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
82 次代码提交
version3.3
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version3.4
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10
Dockerfile
10
Dockerfile
@@ -10,12 +10,16 @@ RUN echo '[global]' > /etc/pip.conf && \
|
|||||||
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||||||
WORKDIR /gpt
|
WORKDIR /gpt
|
||||||
|
|
||||||
# 装载项目文件
|
|
||||||
COPY . .
|
|
||||||
|
|
||||||
# 安装依赖
|
# 安装依赖
|
||||||
|
COPY requirements.txt ./
|
||||||
|
COPY ./docs/gradio-3.32.2-py3-none-any.whl ./docs/gradio-3.32.2-py3-none-any.whl
|
||||||
|
RUN pip3 install -r requirements.txt
|
||||||
|
# 装载项目文件
|
||||||
|
COPY . .
|
||||||
RUN pip3 install -r requirements.txt
|
RUN pip3 install -r requirements.txt
|
||||||
|
|
||||||
|
|
||||||
# 可选步骤，用于预热模块
|
# 可选步骤，用于预热模块
|
||||||
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
|
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
|
||||||
|
|||||||
35
README.md
35
README.md
@@ -1,8 +1,8 @@
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|||||||
> **Note**
|
> **Note**
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||||||
>
|
>
|
||||||
> 安装依赖时，请严格选择requirements.txt中**指定的版本**，并使用官方pip源：
|
> 2023.5.27 对Gradio依赖进行了调整，Fork并解决了官方Gradio的若干Bugs。请及时**更新代码**并重新更新pip依赖。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://pypi.org/simple`
|
> `pip install -r requirements.txt`
|
||||||
>
|
>
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||||||
|
|
||||||
# <img src="docs/logo.png" width="40" > GPT 学术优化 (GPT Academic)
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# <img src="docs/logo.png" width="40" > GPT 学术优化 (GPT Academic)
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||||||
@@ -43,6 +43,7 @@ chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
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|||||||
[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
|
[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/)
|
[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
|
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
|
||||||
|
Arxiv论文精密翻译 | [函数插件] 一键[以超高质量翻译arxiv论文](https://www.bilibili.com/video/BV1dz4y1v77A/)，迄今为止最好的论文翻译工具
|
||||||
公式/图片/表格显示 | 可以同时显示公式的[tex形式和渲染形式](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png)，支持公式、代码高亮
|
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
|
多线程函数插件支持 | 支持多线调用chatgpt，一键处理[海量文本](https://www.bilibili.com/video/BV1FT411H7c5/)或程序
|
||||||
启动暗色gradio[主题](https://github.com/binary-husky/chatgpt_academic/issues/173) | 在浏览器url后面添加```/?__theme=dark```可以切换dark主题
|
启动暗色gradio[主题](https://github.com/binary-husky/chatgpt_academic/issues/173) | 在浏览器url后面添加```/?__theme=dark```可以切换dark主题
|
||||||
@@ -175,21 +176,26 @@ docker-compose up
|
|||||||
|
|
||||||
|
|
||||||
## 安装-方法3：其他部署姿势
|
## 安装-方法3：其他部署姿势
|
||||||
|
1. 一键运行脚本。
|
||||||
|
完全不熟悉python环境的Windows用户可以下载[Release](https://github.com/binary-husky/gpt_academic/releases)中发布的一键运行脚本安装无本地模型的版本，
|
||||||
|
不建议电脑上已有python的用户采用此方法（在此基础上安装插件的依赖很麻烦）。
|
||||||
|
脚本的贡献来源是[oobabooga](https://github.com/oobabooga/one-click-installers)。
|
||||||
|
|
||||||
1. 如何使用反代URL/微软云AzureAPI
|
2. 使用docker-compose运行。
|
||||||
|
请阅读docker-compose.yml后，按照其中的提示操作即可
|
||||||
|
|
||||||
|
3. 如何使用反代URL/微软云AzureAPI。
|
||||||
按照`config.py`中的说明配置API_URL_REDIRECT即可。
|
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）
|
4. 远程云服务器部署（需要云服务器知识与经验）。
|
||||||
请访问[部署wiki-1](https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BA%91%E6%9C%8D%E5%8A%A1%E5%99%A8%E8%BF%9C%E7%A8%8B%E9%83%A8%E7%BD%B2%E6%8C%87%E5%8D%97)
|
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)
|
||||||
|
|
||||||
3. 使用WSL2（Windows Subsystem for Linux 子系统）
|
5. 使用WSL2（Windows Subsystem for Linux 子系统）。
|
||||||
请访问[部署wiki-2](https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BD%BF%E7%94%A8WSL2%EF%BC%88Windows-Subsystem-for-Linux-%E5%AD%90%E7%B3%BB%E7%BB%9F%EF%BC%89%E9%83%A8%E7%BD%B2)
|
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)
|
||||||
|
|
||||||
4. 如何在二级网址（如`http://localhost/subpath`）下运行
|
6. 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)
|
请访问[FastAPI运行说明](docs/WithFastapi.md)
|
||||||
|
|
||||||
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
|
|
||||||
---
|
---
|
||||||
# Advanced Usage
|
# Advanced Usage
|
||||||
## 自定义新的便捷按钮 / 自定义函数插件
|
## 自定义新的便捷按钮 / 自定义函数插件
|
||||||
@@ -278,13 +284,19 @@ Tip：不指定文件直接点击 `载入对话历史存档` 可以查看历史h
|
|||||||
|
|
||||||
10. Latex全文校对纠错
|
10. Latex全文校对纠错
|
||||||
<div align="center">
|
<div align="center">
|
||||||
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/651ccd98-02c9-4464-91e1-77a6b7d1b033" width="500" >
|
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/651ccd98-02c9-4464-91e1-77a6b7d1b033" height="250" > ===>
|
||||||
|
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/476f66d9-7716-4537-b5c1-735372c25adb" height="250">
|
||||||
</div>
|
</div>
|
||||||
|
|
||||||
|
10. Latex/Arxiv论文翻译功能
|
||||||
|
<div align="center">
|
||||||
|
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/002a1a75-ace0-4e6a-94e2-ec1406a746f1" height="250" >
|
||||||
|
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/9fdcc391-f823-464f-9322-f8719677043b" height="250" >
|
||||||
|
</div>
|
||||||
|
|
||||||
## 版本:
|
## 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 3.5(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 3.4: +arxiv论文翻译、latex论文批改功能
|
||||||
- version 3.3: +互联网信息综合功能
|
- 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 3.2: 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 3.1: 支持同时问询多个gpt模型！支持api2d，支持多个apikey负载均衡
|
||||||
@@ -302,7 +314,7 @@ gpt_academic开发者QQ群-2：610599535
|
|||||||
|
|
||||||
- 已知问题
|
- 已知问题
|
||||||
- 某些浏览器翻译插件干扰此软件前端的运行
|
- 某些浏览器翻译插件干扰此软件前端的运行
|
||||||
- gradio版本过高或过低，都会导致多种异常
|
- 官方Gradio目前有很多兼容性Bug，请务必使用requirement.txt安装Gradio
|
||||||
|
|
||||||
## 参考与学习
|
## 参考与学习
|
||||||
|
|
||||||
@@ -327,4 +339,5 @@ https://github.com/kaixindelele/ChatPaper
|
|||||||
# 更多：
|
# 更多：
|
||||||
https://github.com/gradio-app/gradio
|
https://github.com/gradio-app/gradio
|
||||||
https://github.com/fghrsh/live2d_demo
|
https://github.com/fghrsh/live2d_demo
|
||||||
|
https://github.com/oobabooga/one-click-installers
|
||||||
```
|
```
|
||||||
|
|||||||
80
colorful.py
80
colorful.py
@@ -34,58 +34,28 @@ def print亮紫(*kw,**kargs):
|
|||||||
def print亮靛(*kw,**kargs):
|
def print亮靛(*kw,**kargs):
|
||||||
print("\033[1;36m",*kw,"\033[0m",**kargs)
|
print("\033[1;36m",*kw,"\033[0m",**kargs)
|
||||||
|
|
||||||
|
# Do you like the elegance of Chinese characters?
|
||||||
|
def sprint红(*kw):
|
||||||
def print亮红(*kw,**kargs):
|
return "\033[0;31m"+' '.join(kw)+"\033[0m"
|
||||||
print("\033[1;31m",*kw,"\033[0m",**kargs)
|
def sprint绿(*kw):
|
||||||
def print亮绿(*kw,**kargs):
|
return "\033[0;32m"+' '.join(kw)+"\033[0m"
|
||||||
print("\033[1;32m",*kw,"\033[0m",**kargs)
|
def sprint黄(*kw):
|
||||||
def print亮黄(*kw,**kargs):
|
return "\033[0;33m"+' '.join(kw)+"\033[0m"
|
||||||
print("\033[1;33m",*kw,"\033[0m",**kargs)
|
def sprint蓝(*kw):
|
||||||
def print亮蓝(*kw,**kargs):
|
return "\033[0;34m"+' '.join(kw)+"\033[0m"
|
||||||
print("\033[1;34m",*kw,"\033[0m",**kargs)
|
def sprint紫(*kw):
|
||||||
def print亮紫(*kw,**kargs):
|
return "\033[0;35m"+' '.join(kw)+"\033[0m"
|
||||||
print("\033[1;35m",*kw,"\033[0m",**kargs)
|
def sprint靛(*kw):
|
||||||
def print亮靛(*kw,**kargs):
|
return "\033[0;36m"+' '.join(kw)+"\033[0m"
|
||||||
print("\033[1;36m",*kw,"\033[0m",**kargs)
|
def sprint亮红(*kw):
|
||||||
|
return "\033[1;31m"+' '.join(kw)+"\033[0m"
|
||||||
print_red = print红
|
def sprint亮绿(*kw):
|
||||||
print_green = print绿
|
return "\033[1;32m"+' '.join(kw)+"\033[0m"
|
||||||
print_yellow = print黄
|
def sprint亮黄(*kw):
|
||||||
print_blue = print蓝
|
return "\033[1;33m"+' '.join(kw)+"\033[0m"
|
||||||
print_purple = print紫
|
def sprint亮蓝(*kw):
|
||||||
print_indigo = print靛
|
return "\033[1;34m"+' '.join(kw)+"\033[0m"
|
||||||
|
def sprint亮紫(*kw):
|
||||||
print_bold_red = print亮红
|
return "\033[1;35m"+' '.join(kw)+"\033[0m"
|
||||||
print_bold_green = print亮绿
|
def sprint亮靛(*kw):
|
||||||
print_bold_yellow = print亮黄
|
return "\033[1;36m"+' '.join(kw)+"\033[0m"
|
||||||
print_bold_blue = print亮蓝
|
|
||||||
print_bold_purple = print亮紫
|
|
||||||
print_bold_indigo = print亮靛
|
|
||||||
|
|
||||||
if not stdout.isatty():
|
|
||||||
# redirection, avoid a fucked up log file
|
|
||||||
print红 = print
|
|
||||||
print绿 = print
|
|
||||||
print黄 = print
|
|
||||||
print蓝 = print
|
|
||||||
print紫 = print
|
|
||||||
print靛 = print
|
|
||||||
print亮红 = print
|
|
||||||
print亮绿 = print
|
|
||||||
print亮黄 = print
|
|
||||||
print亮蓝 = print
|
|
||||||
print亮紫 = print
|
|
||||||
print亮靛 = print
|
|
||||||
print_red = print
|
|
||||||
print_green = print
|
|
||||||
print_yellow = print
|
|
||||||
print_blue = print
|
|
||||||
print_purple = print
|
|
||||||
print_indigo = print
|
|
||||||
print_bold_red = print
|
|
||||||
print_bold_green = print
|
|
||||||
print_bold_yellow = print
|
|
||||||
print_bold_blue = print
|
|
||||||
print_bold_purple = print
|
|
||||||
print_bold_indigo = print
|
|
||||||
|
|||||||
@@ -126,7 +126,7 @@ def get_crazy_functions():
|
|||||||
###################### 第二组插件 ###########################
|
###################### 第二组插件 ###########################
|
||||||
# [第二组插件]: 经过充分测试
|
# [第二组插件]: 经过充分测试
|
||||||
from crazy_functions.批量总结PDF文档 import 批量总结PDF文档
|
from crazy_functions.批量总结PDF文档 import 批量总结PDF文档
|
||||||
from crazy_functions.批量总结PDF文档pdfminer import 批量总结PDF文档pdfminer
|
# from crazy_functions.批量总结PDF文档pdfminer import 批量总结PDF文档pdfminer
|
||||||
from crazy_functions.批量翻译PDF文档_多线程 import 批量翻译PDF文档
|
from crazy_functions.批量翻译PDF文档_多线程 import 批量翻译PDF文档
|
||||||
from crazy_functions.谷歌检索小助手 import 谷歌检索小助手
|
from crazy_functions.谷歌检索小助手 import 谷歌检索小助手
|
||||||
from crazy_functions.理解PDF文档内容 import 理解PDF文档内容标准文件输入
|
from crazy_functions.理解PDF文档内容 import 理解PDF文档内容标准文件输入
|
||||||
@@ -152,17 +152,16 @@ def get_crazy_functions():
|
|||||||
# 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
|
# 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(批量总结PDF文档)
|
"Function": HotReload(批量总结PDF文档)
|
||||||
},
|
},
|
||||||
"[测试功能] 批量总结PDF文档pdfminer": {
|
# "[测试功能] 批量总结PDF文档pdfminer": {
|
||||||
"Color": "stop",
|
# "Color": "stop",
|
||||||
"AsButton": False, # 加入下拉菜单中
|
# "AsButton": False, # 加入下拉菜单中
|
||||||
"Function": HotReload(批量总结PDF文档pdfminer)
|
# "Function": HotReload(批量总结PDF文档pdfminer)
|
||||||
},
|
# },
|
||||||
"谷歌学术检索助手（输入谷歌学术搜索页url）": {
|
"谷歌学术检索助手（输入谷歌学术搜索页url）": {
|
||||||
"Color": "stop",
|
"Color": "stop",
|
||||||
"AsButton": False, # 加入下拉菜单中
|
"AsButton": False, # 加入下拉菜单中
|
||||||
"Function": HotReload(谷歌检索小助手)
|
"Function": HotReload(谷歌检索小助手)
|
||||||
},
|
},
|
||||||
|
|
||||||
"理解PDF文档内容 （模仿ChatPDF）": {
|
"理解PDF文档内容 （模仿ChatPDF）": {
|
||||||
# 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
|
# 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",
|
"Color": "stop",
|
||||||
@@ -181,7 +180,7 @@ def get_crazy_functions():
|
|||||||
"AsButton": False, # 加入下拉菜单中
|
"AsButton": False, # 加入下拉菜单中
|
||||||
"Function": HotReload(Latex英文纠错)
|
"Function": HotReload(Latex英文纠错)
|
||||||
},
|
},
|
||||||
"[测试功能] 中文Latex项目全文润色（输入路径或上传压缩包）": {
|
"中文Latex项目全文润色（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
|
# 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",
|
"Color": "stop",
|
||||||
"AsButton": False, # 加入下拉菜单中
|
"AsButton": False, # 加入下拉菜单中
|
||||||
@@ -210,65 +209,88 @@ def get_crazy_functions():
|
|||||||
})
|
})
|
||||||
|
|
||||||
###################### 第三组插件 ###########################
|
###################### 第三组插件 ###########################
|
||||||
# [第三组插件]: 尚未充分测试的函数插件，放在这里
|
# [第三组插件]: 尚未充分测试的函数插件
|
||||||
from crazy_functions.下载arxiv论文翻译摘要 import 下载arxiv论文并翻译摘要
|
|
||||||
function_plugins.update({
|
|
||||||
"一键下载arxiv论文并翻译摘要（先在input输入编号，如1812.10695）": {
|
|
||||||
"Color": "stop",
|
|
||||||
"AsButton": False, # 加入下拉菜单中
|
|
||||||
"Function": HotReload(下载arxiv论文并翻译摘要)
|
|
||||||
}
|
|
||||||
})
|
|
||||||
|
|
||||||
from crazy_functions.联网的ChatGPT import 连接网络回答问题
|
try:
|
||||||
function_plugins.update({
|
from crazy_functions.下载arxiv论文翻译摘要 import 下载arxiv论文并翻译摘要
|
||||||
"连接网络回答问题（先输入问题，再点击按钮，需要访问谷歌）": {
|
function_plugins.update({
|
||||||
"Color": "stop",
|
"一键下载arxiv论文并翻译摘要（先在input输入编号，如1812.10695）": {
|
||||||
"AsButton": False, # 加入下拉菜单中
|
"Color": "stop",
|
||||||
"Function": HotReload(连接网络回答问题)
|
"AsButton": False, # 加入下拉菜单中
|
||||||
}
|
"Function": HotReload(下载arxiv论文并翻译摘要)
|
||||||
})
|
}
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
|
|
||||||
|
try:
|
||||||
|
from crazy_functions.联网的ChatGPT import 连接网络回答问题
|
||||||
|
function_plugins.update({
|
||||||
|
"连接网络回答问题（先输入问题，再点击按钮，需要访问谷歌）": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False, # 加入下拉菜单中
|
||||||
|
"Function": HotReload(连接网络回答问题)
|
||||||
|
}
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
|
|
||||||
|
try:
|
||||||
|
from crazy_functions.解析项目源代码 import 解析任意code项目
|
||||||
|
function_plugins.update({
|
||||||
|
"解析项目源代码（手动指定和筛选源代码文件类型）": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False,
|
||||||
|
"AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
|
||||||
|
"ArgsReminder": "输入时用逗号隔开, *代表通配符, 加了^代表不匹配; 不输入代表全部匹配。例如: \"*.c, ^*.cpp, config.toml, ^*.toml\"", # 高级参数输入区的显示提示
|
||||||
|
"Function": HotReload(解析任意code项目)
|
||||||
|
},
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
|
|
||||||
|
try:
|
||||||
|
from crazy_functions.询问多个大语言模型 import 同时问询_指定模型
|
||||||
|
function_plugins.update({
|
||||||
|
"询问多个GPT模型（手动指定询问哪些模型）": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False,
|
||||||
|
"AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
|
||||||
|
"ArgsReminder": "支持任意数量的llm接口，用&符号分隔。例如chatglm&gpt-3.5-turbo&api2d-gpt-4", # 高级参数输入区的显示提示
|
||||||
|
"Function": HotReload(同时问询_指定模型)
|
||||||
|
},
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
|
|
||||||
|
try:
|
||||||
|
from crazy_functions.图片生成 import 图片生成
|
||||||
|
function_plugins.update({
|
||||||
|
"图片生成（先切换模型到openai或api2d）": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False,
|
||||||
|
"AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
|
||||||
|
"ArgsReminder": "在这里输入分辨率, 如256x256（默认）", # 高级参数输入区的显示提示
|
||||||
|
"Function": HotReload(图片生成)
|
||||||
|
},
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
|
|
||||||
|
try:
|
||||||
|
from crazy_functions.总结音视频 import 总结音视频
|
||||||
|
function_plugins.update({
|
||||||
|
"批量总结音视频（输入路径或上传压缩包）": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False,
|
||||||
|
"AdvancedArgs": True,
|
||||||
|
"ArgsReminder": "调用openai api 使用whisper-1模型, 目前支持的格式:mp4, m4a, wav, mpga, mpeg, mp3。此处可以输入解析提示，例如：解析为简体中文（默认）。",
|
||||||
|
"Function": HotReload(总结音视频)
|
||||||
|
}
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
|
|
||||||
from crazy_functions.解析项目源代码 import 解析任意code项目
|
|
||||||
function_plugins.update({
|
|
||||||
"解析项目源代码（手动指定和筛选源代码文件类型）": {
|
|
||||||
"Color": "stop",
|
|
||||||
"AsButton": False,
|
|
||||||
"AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
|
|
||||||
"ArgsReminder": "输入时用逗号隔开, *代表通配符, 加了^代表不匹配; 不输入代表全部匹配。例如: \"*.c, ^*.cpp, config.toml, ^*.toml\"", # 高级参数输入区的显示提示
|
|
||||||
"Function": HotReload(解析任意code项目)
|
|
||||||
},
|
|
||||||
})
|
|
||||||
from crazy_functions.询问多个大语言模型 import 同时问询_指定模型
|
|
||||||
function_plugins.update({
|
|
||||||
"询问多个GPT模型（手动指定询问哪些模型）": {
|
|
||||||
"Color": "stop",
|
|
||||||
"AsButton": False,
|
|
||||||
"AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
|
|
||||||
"ArgsReminder": "支持任意数量的llm接口，用&符号分隔。例如chatglm&gpt-3.5-turbo&api2d-gpt-4", # 高级参数输入区的显示提示
|
|
||||||
"Function": HotReload(同时问询_指定模型)
|
|
||||||
},
|
|
||||||
})
|
|
||||||
from crazy_functions.图片生成 import 图片生成
|
|
||||||
function_plugins.update({
|
|
||||||
"图片生成（先切换模型到openai或api2d）": {
|
|
||||||
"Color": "stop",
|
|
||||||
"AsButton": False,
|
|
||||||
"AdvancedArgs": True, # 调用时，唤起高级参数输入区（默认False）
|
|
||||||
"ArgsReminder": "在这里输入分辨率, 如256x256（默认）", # 高级参数输入区的显示提示
|
|
||||||
"Function": HotReload(图片生成)
|
|
||||||
},
|
|
||||||
})
|
|
||||||
from crazy_functions.总结音视频 import 总结音视频
|
|
||||||
function_plugins.update({
|
|
||||||
"批量总结音视频（输入路径或上传压缩包）": {
|
|
||||||
"Color": "stop",
|
|
||||||
"AsButton": False,
|
|
||||||
"AdvancedArgs": True,
|
|
||||||
"ArgsReminder": "调用openai api 使用whisper-1模型, 目前支持的格式:mp4, m4a, wav, mpga, mpeg, mp3。此处可以输入解析提示，例如：解析为简体中文（默认）。",
|
|
||||||
"Function": HotReload(总结音视频)
|
|
||||||
}
|
|
||||||
})
|
|
||||||
try:
|
try:
|
||||||
from crazy_functions.数学动画生成manim import 动画生成
|
from crazy_functions.数学动画生成manim import 动画生成
|
||||||
function_plugins.update({
|
function_plugins.update({
|
||||||
@@ -295,5 +317,56 @@ def get_crazy_functions():
|
|||||||
except:
|
except:
|
||||||
print('Load function plugin failed')
|
print('Load function plugin failed')
|
||||||
|
|
||||||
|
try:
|
||||||
|
from crazy_functions.Langchain知识库 import 知识库问答
|
||||||
|
function_plugins.update({
|
||||||
|
"[功能尚不稳定] 构建知识库（请先上传文件素材）": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False,
|
||||||
|
"AdvancedArgs": True,
|
||||||
|
"ArgsReminder": "待注入的知识库名称id, 默认为default",
|
||||||
|
"Function": HotReload(知识库问答)
|
||||||
|
}
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
|
|
||||||
|
try:
|
||||||
|
from crazy_functions.Langchain知识库 import 读取知识库作答
|
||||||
|
function_plugins.update({
|
||||||
|
"[功能尚不稳定] 知识库问答": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False,
|
||||||
|
"AdvancedArgs": True,
|
||||||
|
"ArgsReminder": "待提取的知识库名称id, 默认为default, 您需要首先调用构建知识库",
|
||||||
|
"Function": HotReload(读取知识库作答)
|
||||||
|
}
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
|
|
||||||
|
try:
|
||||||
|
from crazy_functions.Latex输出PDF结果 import Latex英文纠错加PDF对比
|
||||||
|
function_plugins.update({
|
||||||
|
"[功能尚不稳定] Latex英文纠错+LatexDiff高亮修正位置": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False,
|
||||||
|
# "AdvancedArgs": True,
|
||||||
|
# "ArgsReminder": "",
|
||||||
|
"Function": HotReload(Latex英文纠错加PDF对比)
|
||||||
|
}
|
||||||
|
})
|
||||||
|
from crazy_functions.Latex输出PDF结果 import Latex翻译中文并重新编译PDF
|
||||||
|
function_plugins.update({
|
||||||
|
"[功能尚不稳定] Latex翻译/Arixv翻译+重构PDF": {
|
||||||
|
"Color": "stop",
|
||||||
|
"AsButton": False,
|
||||||
|
# "AdvancedArgs": True,
|
||||||
|
# "ArgsReminder": "",
|
||||||
|
"Function": HotReload(Latex翻译中文并重新编译PDF)
|
||||||
|
}
|
||||||
|
})
|
||||||
|
except:
|
||||||
|
print('Load function plugin failed')
|
||||||
###################### 第n组插件 ###########################
|
###################### 第n组插件 ###########################
|
||||||
return function_plugins
|
return function_plugins
|
||||||
|
|||||||
107
crazy_functions/Langchain知识库.py
普通文件
107
crazy_functions/Langchain知识库.py
普通文件
@@ -0,0 +1,107 @@
|
|||||||
|
from toolbox import CatchException, update_ui, ProxyNetworkActivate
|
||||||
|
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
@CatchException
|
||||||
|
def 知识库问答(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
|
||||||
|
"""
|
||||||
|
history = [] # 清空历史，以免输入溢出
|
||||||
|
chatbot.append(("这是什么功能？", "[Local Message] 从一批文件(txt, md, tex)中读取数据构建知识库, 然后进行问答。"))
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
|
||||||
|
# resolve deps
|
||||||
|
try:
|
||||||
|
from zh_langchain import construct_vector_store
|
||||||
|
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
|
||||||
|
from .crazy_utils import knowledge_archive_interface
|
||||||
|
except Exception as e:
|
||||||
|
chatbot.append(
|
||||||
|
["依赖不足",
|
||||||
|
"导入依赖失败。正在尝试自动安装，请查看终端的输出或耐心等待..."]
|
||||||
|
)
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
from .crazy_utils import try_install_deps
|
||||||
|
try_install_deps(['zh_langchain==0.2.0'])
|
||||||
|
|
||||||
|
# < --------------------读取参数--------------- >
|
||||||
|
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
|
||||||
|
kai_id = plugin_kwargs.get("advanced_arg", 'default')
|
||||||
|
|
||||||
|
# < --------------------读取文件--------------- >
|
||||||
|
file_manifest = []
|
||||||
|
spl = ["txt", "doc", "docx", "email", "epub", "html", "json", "md", "msg", "pdf", "ppt", "pptx", "rtf"]
|
||||||
|
for sp in spl:
|
||||||
|
_, file_manifest_tmp, _ = get_files_from_everything(txt, type=f'.{sp}')
|
||||||
|
file_manifest += file_manifest_tmp
|
||||||
|
|
||||||
|
if len(file_manifest) == 0:
|
||||||
|
chatbot.append(["没有找到任何可读取文件", "当前支持的格式包括: txt, md, docx, pptx, pdf, json等"])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
return
|
||||||
|
|
||||||
|
# < -------------------预热文本向量化模组--------------- >
|
||||||
|
chatbot.append(['<br/>'.join(file_manifest), "正在预热文本向量化模组, 如果是第一次运行, 将消耗较长时间下载中文向量化模型..."])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
print('Checking Text2vec ...')
|
||||||
|
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
|
||||||
|
with ProxyNetworkActivate(): # 临时地激活代理网络
|
||||||
|
HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
|
||||||
|
|
||||||
|
# < -------------------构建知识库--------------- >
|
||||||
|
chatbot.append(['<br/>'.join(file_manifest), "正在构建知识库..."])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
print('Establishing knowledge archive ...')
|
||||||
|
with ProxyNetworkActivate(): # 临时地激活代理网络
|
||||||
|
kai = knowledge_archive_interface()
|
||||||
|
kai.feed_archive(file_manifest=file_manifest, id=kai_id)
|
||||||
|
kai_files = kai.get_loaded_file()
|
||||||
|
kai_files = '<br/>'.join(kai_files)
|
||||||
|
# chatbot.append(['知识库构建成功', "正在将知识库存储至cookie中"])
|
||||||
|
# yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
# chatbot._cookies['langchain_plugin_embedding'] = kai.get_current_archive_id()
|
||||||
|
# chatbot._cookies['lock_plugin'] = 'crazy_functions.Langchain知识库->读取知识库作答'
|
||||||
|
# chatbot.append(['完成', "“根据知识库作答”函数插件已经接管问答系统, 提问吧! 但注意, 您接下来不能再使用其他插件了，刷新页面即可以退出知识库问答模式。"])
|
||||||
|
chatbot.append(['构建完成', f"当前知识库内的有效文件：\n\n---\n\n{kai_files}\n\n---\n\n请切换至“知识库问答”插件进行知识库访问, 或者使用此插件继续上传更多文件。"])
|
||||||
|
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
|
||||||
|
|
||||||
|
@CatchException
|
||||||
|
def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port=-1):
|
||||||
|
# resolve deps
|
||||||
|
try:
|
||||||
|
from zh_langchain import construct_vector_store
|
||||||
|
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
|
||||||
|
from .crazy_utils import knowledge_archive_interface
|
||||||
|
except Exception as e:
|
||||||
|
chatbot.append(["依赖不足", "导入依赖失败。正在尝试自动安装，请查看终端的输出或耐心等待..."])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
from .crazy_utils import try_install_deps
|
||||||
|
try_install_deps(['zh_langchain==0.2.0'])
|
||||||
|
|
||||||
|
# < ------------------- --------------- >
|
||||||
|
kai = knowledge_archive_interface()
|
||||||
|
|
||||||
|
if 'langchain_plugin_embedding' in chatbot._cookies:
|
||||||
|
resp, prompt = kai.answer_with_archive_by_id(txt, chatbot._cookies['langchain_plugin_embedding'])
|
||||||
|
else:
|
||||||
|
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
|
||||||
|
kai_id = plugin_kwargs.get("advanced_arg", 'default')
|
||||||
|
resp, prompt = kai.answer_with_archive_by_id(txt, kai_id)
|
||||||
|
|
||||||
|
chatbot.append((txt, '[Local Message] ' + prompt))
|
||||||
|
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
|
||||||
|
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||||
|
inputs=prompt, inputs_show_user=txt,
|
||||||
|
llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
|
||||||
|
sys_prompt=system_prompt
|
||||||
|
)
|
||||||
|
history.extend((prompt, gpt_say))
|
||||||
|
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
|
||||||
@@ -238,3 +238,6 @@ def Latex英文纠错(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
|
|||||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
return
|
return
|
||||||
yield from 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en', mode='proofread')
|
yield from 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en', mode='proofread')
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|||||||
276
crazy_functions/Latex输出PDF结果.py
普通文件
276
crazy_functions/Latex输出PDF结果.py
普通文件
@@ -0,0 +1,276 @@
|
|||||||
|
from toolbox import update_ui, trimmed_format_exc, get_conf, objdump, objload, promote_file_to_downloadzone
|
||||||
|
from toolbox import CatchException, report_execption, update_ui_lastest_msg, zip_result, gen_time_str
|
||||||
|
import glob, os, requests, time
|
||||||
|
pj = os.path.join
|
||||||
|
ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")
|
||||||
|
|
||||||
|
# =================================== 工具函数 ===============================================
|
||||||
|
沙雕GPT啊别犯这些低级翻译错误 = 'You must to translate "agent" to "智能体". '
|
||||||
|
def switch_prompt(pfg, mode):
|
||||||
|
"""
|
||||||
|
Generate prompts and system prompts based on the mode for proofreading or translating.
|
||||||
|
Args:
|
||||||
|
- pfg: Proofreader or Translator instance.
|
||||||
|
- mode: A string specifying the mode, either 'proofread' or 'translate_zh'.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
- inputs_array: A list of strings containing prompts for users to respond to.
|
||||||
|
- sys_prompt_array: A list of strings containing prompts for system prompts.
|
||||||
|
"""
|
||||||
|
n_split = len(pfg.sp_file_contents)
|
||||||
|
if mode == 'proofread':
|
||||||
|
inputs_array = [r"Below is a section from an academic paper, proofread this section." +
|
||||||
|
r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " +
|
||||||
|
r"Answer me only with the revised text:" +
|
||||||
|
f"\n\n{frag}" for frag in pfg.sp_file_contents]
|
||||||
|
sys_prompt_array = ["You are a professional academic paper writer." for _ in range(n_split)]
|
||||||
|
elif mode == 'translate_zh':
|
||||||
|
inputs_array = [r"Below is a section from an English academic paper, translate it into Chinese." + 沙雕GPT啊别犯这些低级翻译错误 +
|
||||||
|
r"Do not modify any latex command such as \section, \cite, \begin, \item and equations. " +
|
||||||
|
r"Answer me only with the translated text:" +
|
||||||
|
f"\n\n{frag}" for frag in pfg.sp_file_contents]
|
||||||
|
sys_prompt_array = ["You are a professional translator." for _ in range(n_split)]
|
||||||
|
else:
|
||||||
|
assert False, "未知指令"
|
||||||
|
return inputs_array, sys_prompt_array
|
||||||
|
|
||||||
|
def desend_to_extracted_folder_if_exist(project_folder):
|
||||||
|
"""
|
||||||
|
Descend into the extracted folder if it exists, otherwise return the original folder.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
- project_folder: A string specifying the folder path.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
- A string specifying the path to the extracted folder, or the original folder if there is no extracted folder.
|
||||||
|
"""
|
||||||
|
maybe_dir = [f for f in glob.glob(f'{project_folder}/*') if os.path.isdir(f)]
|
||||||
|
if len(maybe_dir) == 0: return project_folder
|
||||||
|
if maybe_dir[0].endswith('.extract'): return maybe_dir[0]
|
||||||
|
return project_folder
|
||||||
|
|
||||||
|
def move_project(project_folder, arxiv_id=None):
|
||||||
|
"""
|
||||||
|
Create a new work folder and copy the project folder to it.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
- project_folder: A string specifying the folder path of the project.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
- A string specifying the path to the new work folder.
|
||||||
|
"""
|
||||||
|
import shutil, time
|
||||||
|
time.sleep(2) # avoid time string conflict
|
||||||
|
if arxiv_id is not None:
|
||||||
|
new_workfolder = pj(ARXIV_CACHE_DIR, arxiv_id, 'workfolder')
|
||||||
|
else:
|
||||||
|
new_workfolder = f'gpt_log/{gen_time_str()}'
|
||||||
|
try:
|
||||||
|
shutil.rmtree(new_workfolder)
|
||||||
|
except:
|
||||||
|
pass
|
||||||
|
shutil.copytree(src=project_folder, dst=new_workfolder)
|
||||||
|
return new_workfolder
|
||||||
|
|
||||||
|
def arxiv_download(chatbot, history, txt):
|
||||||
|
def check_cached_translation_pdf(arxiv_id):
|
||||||
|
translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'translation')
|
||||||
|
if not os.path.exists(translation_dir):
|
||||||
|
os.makedirs(translation_dir)
|
||||||
|
target_file = pj(translation_dir, 'translate_zh.pdf')
|
||||||
|
if os.path.exists(target_file):
|
||||||
|
promote_file_to_downloadzone(target_file)
|
||||||
|
return target_file
|
||||||
|
return False
|
||||||
|
def is_float(s):
|
||||||
|
try:
|
||||||
|
float(s)
|
||||||
|
return True
|
||||||
|
except ValueError:
|
||||||
|
return False
|
||||||
|
if ('.' in txt) and ('/' not in txt) and is_float(txt):
|
||||||
|
txt = 'https://arxiv.org/abs/' + txt
|
||||||
|
if not txt.startswith('https://arxiv.org'):
|
||||||
|
return txt, None
|
||||||
|
|
||||||
|
# <-------------- inspect format ------------->
|
||||||
|
chatbot.append([f"检测到arxiv文档连接", '尝试下载 ...'])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history)
|
||||||
|
time.sleep(1) # 刷新界面
|
||||||
|
|
||||||
|
url_ = txt # https://arxiv.org/abs/1707.06690
|
||||||
|
if not txt.startswith('https://arxiv.org/abs/'):
|
||||||
|
msg = f"解析arxiv网址失败, 期望格式例如: https://arxiv.org/abs/1707.06690。实际得到格式: {url_}"
|
||||||
|
yield from update_ui_lastest_msg(msg, chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
return msg, None
|
||||||
|
# <-------------- set format ------------->
|
||||||
|
arxiv_id = url_.split('/abs/')[-1]
|
||||||
|
cached_translation_pdf = check_cached_translation_pdf(arxiv_id)
|
||||||
|
if cached_translation_pdf: return cached_translation_pdf, arxiv_id
|
||||||
|
|
||||||
|
url_tar = url_.replace('/abs/', '/e-print/')
|
||||||
|
translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'e-print')
|
||||||
|
extract_dst = pj(ARXIV_CACHE_DIR, arxiv_id, 'extract')
|
||||||
|
os.makedirs(translation_dir, exist_ok=True)
|
||||||
|
|
||||||
|
# <-------------- download arxiv source file ------------->
|
||||||
|
dst = pj(translation_dir, arxiv_id+'.tar')
|
||||||
|
if os.path.exists(dst):
|
||||||
|
yield from update_ui_lastest_msg("调用缓存", chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
else:
|
||||||
|
yield from update_ui_lastest_msg("开始下载", chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
proxies, = get_conf('proxies')
|
||||||
|
r = requests.get(url_tar, proxies=proxies)
|
||||||
|
with open(dst, 'wb+') as f:
|
||||||
|
f.write(r.content)
|
||||||
|
# <-------------- extract file ------------->
|
||||||
|
yield from update_ui_lastest_msg("下载完成", chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
from toolbox import extract_archive
|
||||||
|
extract_archive(file_path=dst, dest_dir=extract_dst)
|
||||||
|
return extract_dst, arxiv_id
|
||||||
|
# ========================================= 插件主程序1 =====================================================
|
||||||
|
|
||||||
|
|
||||||
|
@CatchException
|
||||||
|
def Latex英文纠错加PDF对比(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||||
|
# <-------------- information about this plugin ------------->
|
||||||
|
chatbot.append([ "函数插件功能？",
|
||||||
|
"对整个Latex项目进行纠错, 用latex编译为PDF对修正处做高亮。函数插件贡献者: Binary-Husky。注意事项: 目前仅支持GPT3.5/GPT4，其他模型转化效果未知。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。仅在Windows系统进行了测试，其他操作系统表现未知。"])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- check deps ------------->
|
||||||
|
try:
|
||||||
|
import glob, os, time, subprocess
|
||||||
|
subprocess.Popen(['pdflatex', '-version'])
|
||||||
|
from .latex_utils import Latex精细分解与转化, 编译Latex
|
||||||
|
except Exception as e:
|
||||||
|
chatbot.append([ f"解析项目: {txt}",
|
||||||
|
f"尝试执行Latex指令失败。Latex没有安装, 或者不在环境变量PATH中。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
return
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- clear history and read input ------------->
|
||||||
|
history = []
|
||||||
|
if os.path.exists(txt):
|
||||||
|
project_folder = txt
|
||||||
|
else:
|
||||||
|
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}/**/*.tex', 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.tex文件: {txt}")
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
return
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- if is a zip/tar file ------------->
|
||||||
|
project_folder = desend_to_extracted_folder_if_exist(project_folder)
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- move latex project away from temp folder ------------->
|
||||||
|
project_folder = move_project(project_folder, arxiv_id=None)
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
|
||||||
|
if not os.path.exists(project_folder + '/merge_proofread.tex'):
|
||||||
|
yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread_latex', switch_prompt=switch_prompt)
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- compile PDF ------------->
|
||||||
|
success = yield from 编译Latex(chatbot, history, main_file_original='merge', main_file_modified='merge_proofread',
|
||||||
|
work_folder_original=project_folder, work_folder_modified=project_folder, work_folder=project_folder)
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- zip PDF ------------->
|
||||||
|
zip_result(project_folder)
|
||||||
|
if success:
|
||||||
|
chatbot.append((f"成功啦", '请查收结果（压缩包）...'))
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||||
|
else:
|
||||||
|
chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 也是可读的, 您可以到Github Issue区, 用该压缩包+对话历史存档进行反馈 ...'))
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||||
|
|
||||||
|
# <-------------- we are done ------------->
|
||||||
|
return success
|
||||||
|
|
||||||
|
|
||||||
|
# ========================================= 插件主程序2 =====================================================
|
||||||
|
|
||||||
|
@CatchException
|
||||||
|
def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||||
|
# <-------------- information about this plugin ------------->
|
||||||
|
chatbot.append([
|
||||||
|
"函数插件功能？",
|
||||||
|
"对整个Latex项目进行翻译, 生成中文PDF。函数插件贡献者: Binary-Husky。注意事项: 目前仅支持GPT3.5/GPT4，其他模型转化效果未知。目前对机器学习类文献转化效果最好，其他类型文献转化效果未知。"])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- check deps ------------->
|
||||||
|
try:
|
||||||
|
import glob, os, time, subprocess
|
||||||
|
subprocess.Popen(['pdflatex', '-version'])
|
||||||
|
from .latex_utils import Latex精细分解与转化, 编译Latex
|
||||||
|
except Exception as e:
|
||||||
|
chatbot.append([ f"解析项目: {txt}",
|
||||||
|
f"尝试执行Latex指令失败。Latex没有安装, 或者不在环境变量PATH中。报错信息\n\n```\n\n{trimmed_format_exc()}\n\n```\n\n"])
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
return
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- clear history and read input ------------->
|
||||||
|
history = []
|
||||||
|
txt, arxiv_id = yield from arxiv_download(chatbot, history, txt)
|
||||||
|
if txt.endswith('.pdf'):
|
||||||
|
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"发现已经存在翻译好的PDF文档")
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
return
|
||||||
|
|
||||||
|
|
||||||
|
if os.path.exists(txt):
|
||||||
|
project_folder = txt
|
||||||
|
else:
|
||||||
|
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}/**/*.tex', 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.tex文件: {txt}")
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
return
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- if is a zip/tar file ------------->
|
||||||
|
project_folder = desend_to_extracted_folder_if_exist(project_folder)
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- move latex project away from temp folder ------------->
|
||||||
|
project_folder = move_project(project_folder, arxiv_id)
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- if merge_translate_zh is already generated, skip gpt req ------------->
|
||||||
|
if not os.path.exists(project_folder + '/merge_translate_zh.tex'):
|
||||||
|
yield from Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='translate_zh', switch_prompt=switch_prompt)
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- compile PDF ------------->
|
||||||
|
success = yield from 编译Latex(chatbot, history, main_file_original='merge', main_file_modified='merge_translate_zh',
|
||||||
|
work_folder_original=project_folder, work_folder_modified=project_folder, work_folder=project_folder)
|
||||||
|
|
||||||
|
# <-------------- zip PDF ------------->
|
||||||
|
zip_result(project_folder)
|
||||||
|
if success:
|
||||||
|
chatbot.append((f"成功啦", '请查收结果（压缩包）...'))
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||||
|
else:
|
||||||
|
chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果（压缩包）, 内含已经翻译的Tex文档, 也是可读的, 您可以到Github Issue区, 用该压缩包+对话历史存档进行反馈 ...'))
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||||
|
|
||||||
|
|
||||||
|
# <-------------- we are done ------------->
|
||||||
|
return success
|
||||||
@@ -3,6 +3,8 @@
|
|||||||
这个文件用于函数插件的单元测试
|
这个文件用于函数插件的单元测试
|
||||||
运行方法 python crazy_functions/crazy_functions_test.py
|
运行方法 python crazy_functions/crazy_functions_test.py
|
||||||
"""
|
"""
|
||||||
|
|
||||||
|
# ==============================================================================================================================
|
||||||
|
|
||||||
def validate_path():
|
def validate_path():
|
||||||
import os, sys
|
import os, sys
|
||||||
@@ -10,10 +12,16 @@ def validate_path():
|
|||||||
root_dir_assume = os.path.abspath(os.path.dirname(__file__) + '/..')
|
root_dir_assume = os.path.abspath(os.path.dirname(__file__) + '/..')
|
||||||
os.chdir(root_dir_assume)
|
os.chdir(root_dir_assume)
|
||||||
sys.path.append(root_dir_assume)
|
sys.path.append(root_dir_assume)
|
||||||
|
|
||||||
validate_path() # validate path so you can run from base directory
|
validate_path() # validate path so you can run from base directory
|
||||||
|
|
||||||
|
# ==============================================================================================================================
|
||||||
|
|
||||||
from colorful import *
|
from colorful import *
|
||||||
from toolbox import get_conf, ChatBotWithCookies
|
from toolbox import get_conf, ChatBotWithCookies
|
||||||
|
import contextlib
|
||||||
|
import os
|
||||||
|
import sys
|
||||||
|
from functools import wraps
|
||||||
proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY = \
|
proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, API_KEY = \
|
||||||
get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY')
|
get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'API_KEY')
|
||||||
|
|
||||||
@@ -30,7 +38,43 @@ history = []
|
|||||||
system_prompt = "Serve me as a writing and programming assistant."
|
system_prompt = "Serve me as a writing and programming assistant."
|
||||||
web_port = 1024
|
web_port = 1024
|
||||||
|
|
||||||
|
# ==============================================================================================================================
|
||||||
|
|
||||||
|
def silence_stdout(func):
|
||||||
|
@wraps(func)
|
||||||
|
def wrapper(*args, **kwargs):
|
||||||
|
_original_stdout = sys.stdout
|
||||||
|
sys.stdout = open(os.devnull, 'w')
|
||||||
|
for q in func(*args, **kwargs):
|
||||||
|
sys.stdout = _original_stdout
|
||||||
|
yield q
|
||||||
|
sys.stdout = open(os.devnull, 'w')
|
||||||
|
sys.stdout.close()
|
||||||
|
sys.stdout = _original_stdout
|
||||||
|
return wrapper
|
||||||
|
|
||||||
|
class CLI_Printer():
|
||||||
|
def __init__(self) -> None:
|
||||||
|
self.pre_buf = ""
|
||||||
|
|
||||||
|
def print(self, buf):
|
||||||
|
bufp = ""
|
||||||
|
for index, chat in enumerate(buf):
|
||||||
|
a, b = chat
|
||||||
|
bufp += sprint亮靛('[Me]:' + a) + '\n'
|
||||||
|
bufp += '[GPT]:' + b
|
||||||
|
if index < len(buf)-1:
|
||||||
|
bufp += '\n'
|
||||||
|
|
||||||
|
if self.pre_buf!="" and bufp.startswith(self.pre_buf):
|
||||||
|
print(bufp[len(self.pre_buf):], end='')
|
||||||
|
else:
|
||||||
|
print('\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n'+bufp, end='')
|
||||||
|
self.pre_buf = bufp
|
||||||
|
return
|
||||||
|
|
||||||
|
cli_printer = CLI_Printer()
|
||||||
|
# ==============================================================================================================================
|
||||||
def test_解析一个Python项目():
|
def test_解析一个Python项目():
|
||||||
from crazy_functions.解析项目源代码 import 解析一个Python项目
|
from crazy_functions.解析项目源代码 import 解析一个Python项目
|
||||||
txt = "crazy_functions/test_project/python/dqn"
|
txt = "crazy_functions/test_project/python/dqn"
|
||||||
@@ -116,6 +160,48 @@ def test_Markdown多语言():
|
|||||||
for cookies, cb, hist, msg in Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
for cookies, cb, hist, msg in Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||||
print(cb)
|
print(cb)
|
||||||
|
|
||||||
|
def test_Langchain知识库():
|
||||||
|
from crazy_functions.Langchain知识库 import 知识库问答
|
||||||
|
txt = "./"
|
||||||
|
chatbot = ChatBotWithCookies(llm_kwargs)
|
||||||
|
for cookies, cb, hist, msg in silence_stdout(知识库问答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||||
|
cli_printer.print(cb) # print(cb)
|
||||||
|
|
||||||
|
chatbot = ChatBotWithCookies(cookies)
|
||||||
|
from crazy_functions.Langchain知识库 import 读取知识库作答
|
||||||
|
txt = "What is the installation method？"
|
||||||
|
for cookies, cb, hist, msg in silence_stdout(读取知识库作答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||||
|
cli_printer.print(cb) # print(cb)
|
||||||
|
|
||||||
|
def test_Langchain知识库读取():
|
||||||
|
from crazy_functions.Langchain知识库 import 读取知识库作答
|
||||||
|
txt = "远程云服务器部署？"
|
||||||
|
for cookies, cb, hist, msg in silence_stdout(读取知识库作答)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||||
|
cli_printer.print(cb) # print(cb)
|
||||||
|
|
||||||
|
def test_Latex():
|
||||||
|
from crazy_functions.Latex输出PDF结果 import Latex英文纠错加PDF对比, Latex翻译中文并重新编译PDF
|
||||||
|
|
||||||
|
# txt = r"https://arxiv.org/abs/1706.03762"
|
||||||
|
# txt = r"https://arxiv.org/abs/1902.03185"
|
||||||
|
# txt = r"https://arxiv.org/abs/2305.18290"
|
||||||
|
# txt = r"https://arxiv.org/abs/2305.17608"
|
||||||
|
# txt = r"https://arxiv.org/abs/2211.16068" # ACE
|
||||||
|
# txt = r"C:\Users\x\arxiv_cache\2211.16068\workfolder" # ACE
|
||||||
|
txt = r"https://arxiv.org/abs/2002.09253"
|
||||||
|
for cookies, cb, hist, msg in (Latex翻译中文并重新编译PDF)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||||
|
cli_printer.print(cb) # print(cb)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
# txt = "2302.02948.tar"
|
||||||
|
# print(txt)
|
||||||
|
# main_tex, work_folder = Latex预处理(txt)
|
||||||
|
# print('main tex:', main_tex)
|
||||||
|
# res = 编译Latex(main_tex, work_folder)
|
||||||
|
# # for cookies, cb, hist, msg in silence_stdout(编译Latex)(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||||
|
# cli_printer.print(cb) # print(cb)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
# test_解析一个Python项目()
|
# test_解析一个Python项目()
|
||||||
@@ -129,7 +215,8 @@ def test_Markdown多语言():
|
|||||||
# test_联网回答问题()
|
# test_联网回答问题()
|
||||||
# test_解析ipynb文件()
|
# test_解析ipynb文件()
|
||||||
# test_数学动画生成manim()
|
# test_数学动画生成manim()
|
||||||
test_Markdown多语言()
|
# test_Langchain知识库()
|
||||||
|
# test_Langchain知识库读取()
|
||||||
|
test_Latex()
|
||||||
input("程序完成，回车退出。")
|
input("程序完成，回车退出。")
|
||||||
print("退出。")
|
print("退出。")
|
||||||
@@ -1,4 +1,5 @@
|
|||||||
from toolbox import update_ui, get_conf, trimmed_format_exc
|
from toolbox import update_ui, get_conf, trimmed_format_exc
|
||||||
|
import threading
|
||||||
|
|
||||||
def input_clipping(inputs, history, max_token_limit):
|
def input_clipping(inputs, history, max_token_limit):
|
||||||
import numpy as np
|
import numpy as np
|
||||||
@@ -606,3 +607,94 @@ def get_files_from_everything(txt, type): # type='.md'
|
|||||||
success = False
|
success = False
|
||||||
|
|
||||||
return success, file_manifest, project_folder
|
return success, file_manifest, project_folder
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def Singleton(cls):
|
||||||
|
_instance = {}
|
||||||
|
|
||||||
|
def _singleton(*args, **kargs):
|
||||||
|
if cls not in _instance:
|
||||||
|
_instance[cls] = cls(*args, **kargs)
|
||||||
|
return _instance[cls]
|
||||||
|
|
||||||
|
return _singleton
|
||||||
|
|
||||||
|
|
||||||
|
@Singleton
|
||||||
|
class knowledge_archive_interface():
|
||||||
|
def __init__(self) -> None:
|
||||||
|
self.threadLock = threading.Lock()
|
||||||
|
self.current_id = ""
|
||||||
|
self.kai_path = None
|
||||||
|
self.qa_handle = None
|
||||||
|
self.text2vec_large_chinese = None
|
||||||
|
|
||||||
|
def get_chinese_text2vec(self):
|
||||||
|
if self.text2vec_large_chinese is None:
|
||||||
|
# < -------------------预热文本向量化模组--------------- >
|
||||||
|
from toolbox import ProxyNetworkActivate
|
||||||
|
print('Checking Text2vec ...')
|
||||||
|
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
|
||||||
|
with ProxyNetworkActivate(): # 临时地激活代理网络
|
||||||
|
self.text2vec_large_chinese = HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
|
||||||
|
|
||||||
|
return self.text2vec_large_chinese
|
||||||
|
|
||||||
|
|
||||||
|
def feed_archive(self, file_manifest, id="default"):
|
||||||
|
self.threadLock.acquire()
|
||||||
|
# import uuid
|
||||||
|
self.current_id = id
|
||||||
|
from zh_langchain import construct_vector_store
|
||||||
|
self.qa_handle, self.kai_path = construct_vector_store(
|
||||||
|
vs_id=self.current_id,
|
||||||
|
files=file_manifest,
|
||||||
|
sentence_size=100,
|
||||||
|
history=[],
|
||||||
|
one_conent="",
|
||||||
|
one_content_segmentation="",
|
||||||
|
text2vec = self.get_chinese_text2vec(),
|
||||||
|
)
|
||||||
|
self.threadLock.release()
|
||||||
|
|
||||||
|
def get_current_archive_id(self):
|
||||||
|
return self.current_id
|
||||||
|
|
||||||
|
def get_loaded_file(self):
|
||||||
|
return self.qa_handle.get_loaded_file()
|
||||||
|
|
||||||
|
def answer_with_archive_by_id(self, txt, id):
|
||||||
|
self.threadLock.acquire()
|
||||||
|
if not self.current_id == id:
|
||||||
|
self.current_id = id
|
||||||
|
from zh_langchain import construct_vector_store
|
||||||
|
self.qa_handle, self.kai_path = construct_vector_store(
|
||||||
|
vs_id=self.current_id,
|
||||||
|
files=[],
|
||||||
|
sentence_size=100,
|
||||||
|
history=[],
|
||||||
|
one_conent="",
|
||||||
|
one_content_segmentation="",
|
||||||
|
text2vec = self.get_chinese_text2vec(),
|
||||||
|
)
|
||||||
|
VECTOR_SEARCH_SCORE_THRESHOLD = 0
|
||||||
|
VECTOR_SEARCH_TOP_K = 4
|
||||||
|
CHUNK_SIZE = 512
|
||||||
|
resp, prompt = self.qa_handle.get_knowledge_based_conent_test(
|
||||||
|
query = txt,
|
||||||
|
vs_path = self.kai_path,
|
||||||
|
score_threshold=VECTOR_SEARCH_SCORE_THRESHOLD,
|
||||||
|
vector_search_top_k=VECTOR_SEARCH_TOP_K,
|
||||||
|
chunk_conent=True,
|
||||||
|
chunk_size=CHUNK_SIZE,
|
||||||
|
text2vec = self.get_chinese_text2vec(),
|
||||||
|
)
|
||||||
|
self.threadLock.release()
|
||||||
|
return resp, prompt
|
||||||
|
|
||||||
|
def try_install_deps(deps):
|
||||||
|
for dep in deps:
|
||||||
|
import subprocess, sys
|
||||||
|
subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--user', dep])
|
||||||
|
|||||||
646
crazy_functions/latex_utils.py
普通文件
646
crazy_functions/latex_utils.py
普通文件
@@ -0,0 +1,646 @@
|
|||||||
|
from toolbox import update_ui, update_ui_lastest_msg # 刷新Gradio前端界面
|
||||||
|
from toolbox import zip_folder, objdump, objload, promote_file_to_downloadzone
|
||||||
|
import os, shutil
|
||||||
|
import re
|
||||||
|
import numpy as np
|
||||||
|
pj = os.path.join
|
||||||
|
|
||||||
|
"""
|
||||||
|
========================================================================
|
||||||
|
Part One
|
||||||
|
Latex segmentation to a linklist
|
||||||
|
========================================================================
|
||||||
|
"""
|
||||||
|
PRESERVE = 0
|
||||||
|
TRANSFORM = 1
|
||||||
|
|
||||||
|
def split_worker(text, mask, pattern, flags=0):
|
||||||
|
"""
|
||||||
|
Add a preserve text area in this paper
|
||||||
|
"""
|
||||||
|
pattern_compile = re.compile(pattern, flags)
|
||||||
|
for res in pattern_compile.finditer(text):
|
||||||
|
mask[res.span()[0]:res.span()[1]] = PRESERVE
|
||||||
|
return text, mask
|
||||||
|
|
||||||
|
def split_worker_reverse_caption(text, mask, pattern, flags=0):
|
||||||
|
"""
|
||||||
|
Move caption area out of preserve area
|
||||||
|
"""
|
||||||
|
pattern_compile = re.compile(pattern, flags)
|
||||||
|
for res in pattern_compile.finditer(text):
|
||||||
|
mask[res.regs[1][0]:res.regs[1][1]] = TRANSFORM
|
||||||
|
return text, mask
|
||||||
|
|
||||||
|
def split_worker_begin_end(text, mask, pattern, flags=0, limit_n_lines=42):
|
||||||
|
"""
|
||||||
|
Find all \begin{} ... \end{} text block that with less than limit_n_lines lines.
|
||||||
|
Add it to preserve area
|
||||||
|
"""
|
||||||
|
pattern_compile = re.compile(pattern, flags)
|
||||||
|
def search_with_line_limit(text, mask):
|
||||||
|
for res in pattern_compile.finditer(text):
|
||||||
|
cmd = res.group(1) # begin{what}
|
||||||
|
this = res.group(2) # content between begin and end
|
||||||
|
this_mask = mask[res.regs[2][0]:res.regs[2][1]]
|
||||||
|
white_list = ['document', 'abstract', 'lemma', 'definition', 'sproof',
|
||||||
|
'em', 'emph', 'textit', 'textbf', 'itemize', 'enumerate']
|
||||||
|
if (cmd in white_list) or this.count('\n') >= limit_n_lines: # use a magical number 42
|
||||||
|
this, this_mask = search_with_line_limit(this, this_mask)
|
||||||
|
mask[res.regs[2][0]:res.regs[2][1]] = this_mask
|
||||||
|
else:
|
||||||
|
mask[res.regs[0][0]:res.regs[0][1]] = PRESERVE
|
||||||
|
return text, mask
|
||||||
|
return search_with_line_limit(text, mask)
|
||||||
|
|
||||||
|
class LinkedListNode():
|
||||||
|
"""
|
||||||
|
Linked List Node
|
||||||
|
"""
|
||||||
|
def __init__(self, string, preserve=True) -> None:
|
||||||
|
self.string = string
|
||||||
|
self.preserve = preserve
|
||||||
|
self.next = None
|
||||||
|
# self.begin_line = 0
|
||||||
|
# self.begin_char = 0
|
||||||
|
|
||||||
|
def convert_to_linklist(text, mask):
|
||||||
|
root = LinkedListNode("", preserve=True)
|
||||||
|
current_node = root
|
||||||
|
for c, m, i in zip(text, mask, range(len(text))):
|
||||||
|
if (m==PRESERVE and current_node.preserve) \
|
||||||
|
or (m==TRANSFORM and not current_node.preserve):
|
||||||
|
# add
|
||||||
|
current_node.string += c
|
||||||
|
else:
|
||||||
|
current_node.next = LinkedListNode(c, preserve=(m==PRESERVE))
|
||||||
|
current_node = current_node.next
|
||||||
|
return root
|
||||||
|
"""
|
||||||
|
========================================================================
|
||||||
|
Latex Merge File
|
||||||
|
========================================================================
|
||||||
|
"""
|
||||||
|
|
||||||
|
def 寻找Latex主文件(file_manifest, mode):
|
||||||
|
"""
|
||||||
|
在多Tex文档中，寻找主文件，必须包含documentclass，返回找到的第一个。
|
||||||
|
P.S. 但愿没人把latex模板放在里面传进来
|
||||||
|
"""
|
||||||
|
for texf in file_manifest:
|
||||||
|
if os.path.basename(texf).startswith('merge'):
|
||||||
|
continue
|
||||||
|
with open(texf, 'r', encoding='utf8') as f:
|
||||||
|
file_content = f.read()
|
||||||
|
if r'\documentclass' in file_content:
|
||||||
|
return texf
|
||||||
|
else:
|
||||||
|
continue
|
||||||
|
raise RuntimeError('无法找到一个主Tex文件（包含documentclass关键字）')
|
||||||
|
def rm_comments(main_file):
|
||||||
|
new_file_remove_comment_lines = []
|
||||||
|
for l in main_file.splitlines():
|
||||||
|
# 删除整行的空注释
|
||||||
|
if l.startswith("%") or (l.startswith(" ") and l.lstrip().startswith("%")):
|
||||||
|
pass
|
||||||
|
else:
|
||||||
|
new_file_remove_comment_lines.append(l)
|
||||||
|
main_file = '\n'.join(new_file_remove_comment_lines)
|
||||||
|
main_file = re.sub(r'(?<!\\)%.*', '', main_file) # 使用正则表达式查找半行注释, 并替换为空字符串
|
||||||
|
return main_file
|
||||||
|
def merge_tex_files_(project_foler, main_file, mode):
|
||||||
|
"""
|
||||||
|
Merge Tex project recrusively
|
||||||
|
"""
|
||||||
|
main_file = rm_comments(main_file)
|
||||||
|
for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
|
||||||
|
f = s.group(1)
|
||||||
|
fp = os.path.join(project_foler, f)
|
||||||
|
if os.path.exists(fp):
|
||||||
|
# e.g., \input{srcs/07_appendix.tex}
|
||||||
|
with open(fp, 'r', encoding='utf-8', errors='replace') as fx:
|
||||||
|
c = fx.read()
|
||||||
|
else:
|
||||||
|
# e.g., \input{srcs/07_appendix}
|
||||||
|
with open(fp+'.tex', 'r', encoding='utf-8', errors='replace') as fx:
|
||||||
|
c = fx.read()
|
||||||
|
c = merge_tex_files_(project_foler, c, mode)
|
||||||
|
main_file = main_file[:s.span()[0]] + c + main_file[s.span()[1]:]
|
||||||
|
return main_file
|
||||||
|
|
||||||
|
def merge_tex_files(project_foler, main_file, mode):
|
||||||
|
"""
|
||||||
|
Merge Tex project recrusively
|
||||||
|
P.S. 顺便把CTEX塞进去以支持中文
|
||||||
|
P.S. 顺便把Latex的注释去除
|
||||||
|
"""
|
||||||
|
main_file = merge_tex_files_(project_foler, main_file, mode)
|
||||||
|
main_file = rm_comments(main_file)
|
||||||
|
|
||||||
|
if mode == 'translate_zh':
|
||||||
|
pattern = re.compile(r'\\documentclass.*\n')
|
||||||
|
match = pattern.search(main_file)
|
||||||
|
position = match.end()
|
||||||
|
add_ctex = '\\usepackage{ctex}\n'
|
||||||
|
add_url = '\\usepackage{url}\n' if '{url}' not in main_file else ''
|
||||||
|
main_file = main_file[:position] + add_ctex + add_url + main_file[position:]
|
||||||
|
# 2 fontset=windows
|
||||||
|
import platform
|
||||||
|
if platform.system() != 'Windows':
|
||||||
|
main_file = re.sub(r"\\documentclass\[(.*?)\]{(.*?)}", r"\\documentclass[\1,fontset=windows]{\2}",main_file)
|
||||||
|
main_file = re.sub(r"\\documentclass{(.*?)}", r"\\documentclass[fontset=windows]{\1}",main_file)
|
||||||
|
return main_file
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
"""
|
||||||
|
========================================================================
|
||||||
|
Post process
|
||||||
|
========================================================================
|
||||||
|
"""
|
||||||
|
def mod_inbraket(match):
|
||||||
|
"""
|
||||||
|
为啥chatgpt会把cite里面的逗号换成中文逗号呀
|
||||||
|
"""
|
||||||
|
# get the matched string
|
||||||
|
cmd = match.group(1)
|
||||||
|
str_to_modify = match.group(2)
|
||||||
|
# modify the matched string
|
||||||
|
str_to_modify = str_to_modify.replace('：', ':') # 前面是中文冒号，后面是英文冒号
|
||||||
|
str_to_modify = str_to_modify.replace('，', ',') # 前面是中文逗号，后面是英文逗号
|
||||||
|
# str_to_modify = 'BOOM'
|
||||||
|
return "\\" + cmd + "{" + str_to_modify + "}"
|
||||||
|
|
||||||
|
def fix_content(final_tex, node_string):
|
||||||
|
"""
|
||||||
|
Fix common GPT errors to increase success rate
|
||||||
|
"""
|
||||||
|
final_tex = re.sub(r"(?<!\\)%", "\\%", final_tex)
|
||||||
|
final_tex = re.sub(r"\\([a-z]{2,10})\ \{", r"\\\1{", string=final_tex)
|
||||||
|
final_tex = re.sub(r"\\\ ([a-z]{2,10})\{", r"\\\1{", string=final_tex)
|
||||||
|
final_tex = re.sub(r"\\([a-z]{2,10})\{([^\}]*?)\}", mod_inbraket, string=final_tex)
|
||||||
|
|
||||||
|
if node_string.count('\\begin') != final_tex.count('\\begin'):
|
||||||
|
final_tex = node_string # 出问题了，还原原文
|
||||||
|
if node_string.count('\_') > 0 and node_string.count('\_') > final_tex.count('\_'):
|
||||||
|
# walk and replace any _ without \
|
||||||
|
final_tex = re.sub(r"(?<!\\)_", "\\_", final_tex)
|
||||||
|
if node_string.count('{') != node_string.count('}'):
|
||||||
|
if final_tex.count('{') != node_string.count('{'):
|
||||||
|
final_tex = node_string # 出问题了，还原原文
|
||||||
|
if final_tex.count('}') != node_string.count('}'):
|
||||||
|
final_tex = node_string # 出问题了，还原原文
|
||||||
|
return final_tex
|
||||||
|
|
||||||
|
def split_subprocess(txt, project_folder, return_dict):
|
||||||
|
"""
|
||||||
|
break down latex file to a linked list,
|
||||||
|
each node use a preserve flag to indicate whether it should
|
||||||
|
be proccessed by GPT.
|
||||||
|
"""
|
||||||
|
text = txt
|
||||||
|
mask = np.zeros(len(txt), dtype=np.uint8) + TRANSFORM
|
||||||
|
|
||||||
|
# 吸收title与作者以上的部分
|
||||||
|
text, mask = split_worker(text, mask, r"(.*?)\\maketitle", re.DOTALL)
|
||||||
|
# 删除iffalse注释
|
||||||
|
text, mask = split_worker(text, mask, r"\\iffalse(.*?)\\fi", re.DOTALL)
|
||||||
|
# 吸收在25行以内的begin-end组合
|
||||||
|
text, mask = split_worker_begin_end(text, mask, r"\\begin\{([a-z\*]*)\}(.*?)\\end\{\1\}", re.DOTALL, limit_n_lines=25)
|
||||||
|
# 吸收匿名公式
|
||||||
|
text, mask = split_worker(text, mask, r"\$\$(.*?)\$\$", re.DOTALL)
|
||||||
|
# 吸收其他杂项
|
||||||
|
text, mask = split_worker(text, mask, r"\\section\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\section\*\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\subsection\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\subsubsection\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\bibliography\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\bibliographystyle\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{lstlisting\}(.*?)\\end\{lstlisting\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{wraptable\}(.*?)\\end\{wraptable\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{algorithm\}(.*?)\\end\{algorithm\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{wrapfigure\}(.*?)\\end\{wrapfigure\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{wrapfigure\*\}(.*?)\\end\{wrapfigure\*\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{figure\}(.*?)\\end\{figure\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{figure\*\}(.*?)\\end\{figure\*\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{multline\}(.*?)\\end\{multline\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{multline\*\}(.*?)\\end\{multline\*\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{table\}(.*?)\\end\{table\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{table\*\}(.*?)\\end\{table\*\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{minipage\}(.*?)\\end\{minipage\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{minipage\*\}(.*?)\\end\{minipage\*\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{align\*\}(.*?)\\end\{align\*\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{align\}(.*?)\\end\{align\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{equation\}(.*?)\\end\{equation\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{equation\*\}(.*?)\\end\{equation\*\}", re.DOTALL)
|
||||||
|
text, mask = split_worker(text, mask, r"\\item ")
|
||||||
|
text, mask = split_worker(text, mask, r"\\label\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\begin\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\vspace\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\hspace\{(.*?)\}")
|
||||||
|
text, mask = split_worker(text, mask, r"\\end\{(.*?)\}")
|
||||||
|
# text, mask = split_worker_reverse_caption(text, mask, r"\\caption\{(.*?)\}", re.DOTALL)
|
||||||
|
root = convert_to_linklist(text, mask)
|
||||||
|
|
||||||
|
# 修复括号
|
||||||
|
node = root
|
||||||
|
while True:
|
||||||
|
string = node.string
|
||||||
|
if node.preserve:
|
||||||
|
node = node.next
|
||||||
|
if node is None: break
|
||||||
|
continue
|
||||||
|
def break_check(string):
|
||||||
|
str_stack = [""] # (lv, index)
|
||||||
|
for i, c in enumerate(string):
|
||||||
|
if c == '{':
|
||||||
|
str_stack.append('{')
|
||||||
|
elif c == '}':
|
||||||
|
if len(str_stack) == 1:
|
||||||
|
print('stack fix')
|
||||||
|
return i
|
||||||
|
str_stack.pop(-1)
|
||||||
|
else:
|
||||||
|
str_stack[-1] += c
|
||||||
|
return -1
|
||||||
|
bp = break_check(string)
|
||||||
|
|
||||||
|
if bp == -1:
|
||||||
|
pass
|
||||||
|
elif bp == 0:
|
||||||
|
node.string = string[:1]
|
||||||
|
q = LinkedListNode(string[1:], False)
|
||||||
|
q.next = node.next
|
||||||
|
node.next = q
|
||||||
|
else:
|
||||||
|
node.string = string[:bp]
|
||||||
|
q = LinkedListNode(string[bp:], False)
|
||||||
|
q.next = node.next
|
||||||
|
node.next = q
|
||||||
|
|
||||||
|
node = node.next
|
||||||
|
if node is None: break
|
||||||
|
|
||||||
|
# 屏蔽空行和太短的句子
|
||||||
|
node = root
|
||||||
|
while True:
|
||||||
|
if len(node.string.strip('\n').strip(''))==0: node.preserve = True
|
||||||
|
if len(node.string.strip('\n').strip(''))<42: node.preserve = True
|
||||||
|
node = node.next
|
||||||
|
if node is None: break
|
||||||
|
node = root
|
||||||
|
while True:
|
||||||
|
if node.next and node.preserve and node.next.preserve:
|
||||||
|
node.string += node.next.string
|
||||||
|
node.next = node.next.next
|
||||||
|
node = node.next
|
||||||
|
if node is None: break
|
||||||
|
|
||||||
|
# 将前后断行符脱离
|
||||||
|
node = root
|
||||||
|
prev_node = None
|
||||||
|
while True:
|
||||||
|
if not node.preserve:
|
||||||
|
lstriped_ = node.string.lstrip().lstrip('\n')
|
||||||
|
if (prev_node is not None) and (prev_node.preserve) and (len(lstriped_)!=len(node.string)):
|
||||||
|
prev_node.string += node.string[:-len(lstriped_)]
|
||||||
|
node.string = lstriped_
|
||||||
|
rstriped_ = node.string.rstrip().rstrip('\n')
|
||||||
|
if (node.next is not None) and (node.next.preserve) and (len(rstriped_)!=len(node.string)):
|
||||||
|
node.next.string = node.string[len(rstriped_):] + node.next.string
|
||||||
|
node.string = rstriped_
|
||||||
|
# =====
|
||||||
|
prev_node = node
|
||||||
|
node = node.next
|
||||||
|
if node is None: break
|
||||||
|
|
||||||
|
with open(pj(project_folder, 'debug_log.html'), 'w', encoding='utf8') as f:
|
||||||
|
segment_parts_for_gpt = []
|
||||||
|
nodes = []
|
||||||
|
node = root
|
||||||
|
while True:
|
||||||
|
nodes.append(node)
|
||||||
|
show_html = node.string.replace('\n','<br/>')
|
||||||
|
if not node.preserve:
|
||||||
|
segment_parts_for_gpt.append(node.string)
|
||||||
|
f.write(f'<p style="color:black;">#{show_html}#</p>')
|
||||||
|
else:
|
||||||
|
f.write(f'<p style="color:red;">{show_html}</p>')
|
||||||
|
node = node.next
|
||||||
|
if node is None: break
|
||||||
|
|
||||||
|
for n in nodes: n.next = None # break
|
||||||
|
return_dict['nodes'] = nodes
|
||||||
|
return_dict['segment_parts_for_gpt'] = segment_parts_for_gpt
|
||||||
|
return return_dict
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
class LatexPaperSplit():
|
||||||
|
"""
|
||||||
|
break down latex file to a linked list,
|
||||||
|
each node use a preserve flag to indicate whether it should
|
||||||
|
be proccessed by GPT.
|
||||||
|
"""
|
||||||
|
def __init__(self) -> None:
|
||||||
|
self.nodes = None
|
||||||
|
self.msg = "{\\scriptsize\\textbf{警告：该PDF由GPT-Academic开源项目调用大语言模型+Latex翻译插件一键生成，" + \
|
||||||
|
"版权归原文作者所有。翻译内容可靠性无任何保障，请仔细鉴别并以原文为准。" + \
|
||||||
|
"项目Github地址 \\url{https://github.com/binary-husky/gpt_academic/}。"
|
||||||
|
# 请您不要删除或修改这行警告，除非您是论文的原作者（如果您是论文原作者，欢迎加REAME中的QQ联系开发者）
|
||||||
|
self.msg_declare = "为了防止大语言模型的意外谬误产生扩散影响，禁止移除或修改此警告。}}\\\\"
|
||||||
|
|
||||||
|
def merge_result(self, arr, mode, msg):
|
||||||
|
"""
|
||||||
|
Merge the result after the GPT process completed
|
||||||
|
"""
|
||||||
|
result_string = ""
|
||||||
|
p = 0
|
||||||
|
for node in self.nodes:
|
||||||
|
if node.preserve:
|
||||||
|
result_string += node.string
|
||||||
|
else:
|
||||||
|
result_string += fix_content(arr[p], node.string)
|
||||||
|
p += 1
|
||||||
|
if mode == 'translate_zh':
|
||||||
|
pattern = re.compile(r'\\begin\{abstract\}.*\n')
|
||||||
|
match = pattern.search(result_string)
|
||||||
|
position = match.end()
|
||||||
|
result_string = result_string[:position] + self.msg + msg + self.msg_declare + result_string[position:]
|
||||||
|
return result_string
|
||||||
|
|
||||||
|
def split(self, txt, project_folder):
|
||||||
|
"""
|
||||||
|
break down latex file to a linked list,
|
||||||
|
each node use a preserve flag to indicate whether it should
|
||||||
|
be proccessed by GPT.
|
||||||
|
P.S. use multiprocessing to avoid timeout error
|
||||||
|
"""
|
||||||
|
import multiprocessing
|
||||||
|
manager = multiprocessing.Manager()
|
||||||
|
return_dict = manager.dict()
|
||||||
|
p = multiprocessing.Process(
|
||||||
|
target=split_subprocess,
|
||||||
|
args=(txt, project_folder, return_dict))
|
||||||
|
p.start()
|
||||||
|
p.join()
|
||||||
|
self.nodes = return_dict['nodes']
|
||||||
|
self.sp = return_dict['segment_parts_for_gpt']
|
||||||
|
return self.sp
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
class LatexPaperFileGroup():
|
||||||
|
"""
|
||||||
|
use tokenizer to break down text according to max_token_limit
|
||||||
|
"""
|
||||||
|
def __init__(self):
|
||||||
|
self.file_paths = []
|
||||||
|
self.file_contents = []
|
||||||
|
self.sp_file_contents = []
|
||||||
|
self.sp_file_index = []
|
||||||
|
self.sp_file_tag = []
|
||||||
|
|
||||||
|
# count_token
|
||||||
|
from request_llm.bridge_all import model_info
|
||||||
|
enc = model_info["gpt-3.5-turbo"]['tokenizer']
|
||||||
|
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
|
||||||
|
self.get_token_num = get_token_num
|
||||||
|
|
||||||
|
def run_file_split(self, max_token_limit=1900):
|
||||||
|
"""
|
||||||
|
use tokenizer to break down text according to max_token_limit
|
||||||
|
"""
|
||||||
|
for index, file_content in enumerate(self.file_contents):
|
||||||
|
if self.get_token_num(file_content) < max_token_limit:
|
||||||
|
self.sp_file_contents.append(file_content)
|
||||||
|
self.sp_file_index.append(index)
|
||||||
|
self.sp_file_tag.append(self.file_paths[index])
|
||||||
|
else:
|
||||||
|
from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
|
||||||
|
segments = breakdown_txt_to_satisfy_token_limit_for_pdf(file_content, self.get_token_num, max_token_limit)
|
||||||
|
for j, segment in enumerate(segments):
|
||||||
|
self.sp_file_contents.append(segment)
|
||||||
|
self.sp_file_index.append(index)
|
||||||
|
self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.tex")
|
||||||
|
print('Segmentation: done')
|
||||||
|
|
||||||
|
def merge_result(self):
|
||||||
|
self.file_result = ["" for _ in range(len(self.file_paths))]
|
||||||
|
for r, k in zip(self.sp_file_result, self.sp_file_index):
|
||||||
|
self.file_result[k] += r
|
||||||
|
|
||||||
|
def write_result(self):
|
||||||
|
manifest = []
|
||||||
|
for path, res in zip(self.file_paths, self.file_result):
|
||||||
|
with open(path + '.polish.tex', 'w', encoding='utf8') as f:
|
||||||
|
manifest.append(path + '.polish.tex')
|
||||||
|
f.write(res)
|
||||||
|
return manifest
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def Latex精细分解与转化(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, mode='proofread', switch_prompt=None):
|
||||||
|
import time, os, re
|
||||||
|
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
|
||||||
|
from .latex_utils import LatexPaperFileGroup, merge_tex_files, LatexPaperSplit, 寻找Latex主文件
|
||||||
|
|
||||||
|
# <-------- 寻找主tex文件 ---------->
|
||||||
|
maintex = 寻找Latex主文件(file_manifest, mode)
|
||||||
|
chatbot.append((f"定位主Latex文件", f'[Local Message] 分析结果：该项目的Latex主文件是{maintex}, 如果分析错误, 请立即终止程序, 删除或修改歧义文件, 然后重试。主程序即将开始, 请稍候。'))
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
time.sleep(3)
|
||||||
|
|
||||||
|
# <-------- 读取Latex文件, 将多文件tex工程融合为一个巨型tex ---------->
|
||||||
|
main_tex_basename = os.path.basename(maintex)
|
||||||
|
assert main_tex_basename.endswith('.tex')
|
||||||
|
main_tex_basename_bare = main_tex_basename[:-4]
|
||||||
|
may_exist_bbl = pj(project_folder, f'{main_tex_basename_bare}.bbl')
|
||||||
|
if os.path.exists(may_exist_bbl):
|
||||||
|
shutil.copyfile(may_exist_bbl, pj(project_folder, f'merge.bbl'))
|
||||||
|
shutil.copyfile(may_exist_bbl, pj(project_folder, f'merge_{mode}.bbl'))
|
||||||
|
shutil.copyfile(may_exist_bbl, pj(project_folder, f'merge_diff.bbl'))
|
||||||
|
|
||||||
|
with open(maintex, 'r', encoding='utf-8', errors='replace') as f:
|
||||||
|
content = f.read()
|
||||||
|
merged_content = merge_tex_files(project_folder, content, mode)
|
||||||
|
|
||||||
|
with open(project_folder + '/merge.tex', 'w', encoding='utf-8', errors='replace') as f:
|
||||||
|
f.write(merged_content)
|
||||||
|
|
||||||
|
# <-------- 精细切分latex文件 ---------->
|
||||||
|
lps = LatexPaperSplit()
|
||||||
|
res = lps.split(merged_content, project_folder) # 消耗时间的函数
|
||||||
|
|
||||||
|
# <-------- 拆分过长的latex片段 ---------->
|
||||||
|
pfg = LatexPaperFileGroup()
|
||||||
|
for index, r in enumerate(res):
|
||||||
|
pfg.file_paths.append('segment-' + str(index))
|
||||||
|
pfg.file_contents.append(r)
|
||||||
|
|
||||||
|
pfg.run_file_split(max_token_limit=1024)
|
||||||
|
n_split = len(pfg.sp_file_contents)
|
||||||
|
|
||||||
|
# <-------- 根据需要切换prompt ---------->
|
||||||
|
inputs_array, sys_prompt_array = switch_prompt(pfg, mode)
|
||||||
|
inputs_show_user_array = [f"{mode} {f}" for f in pfg.sp_file_tag]
|
||||||
|
|
||||||
|
if os.path.exists(pj(project_folder,'temp.pkl')):
|
||||||
|
|
||||||
|
# <-------- 【仅调试】如果存在调试缓存文件，则跳过GPT请求环节 ---------->
|
||||||
|
pfg = objload(file=pj(project_folder,'temp.pkl'))
|
||||||
|
|
||||||
|
else:
|
||||||
|
# <-------- gpt 多线程请求 ---------->
|
||||||
|
gpt_response_collection = yield from request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
|
||||||
|
inputs_array=inputs_array,
|
||||||
|
inputs_show_user_array=inputs_show_user_array,
|
||||||
|
llm_kwargs=llm_kwargs,
|
||||||
|
chatbot=chatbot,
|
||||||
|
history_array=[[""] for _ in range(n_split)],
|
||||||
|
sys_prompt_array=sys_prompt_array,
|
||||||
|
# max_workers=5, # 并行任务数量限制, 最多同时执行5个, 其他的排队等待
|
||||||
|
scroller_max_len = 40
|
||||||
|
)
|
||||||
|
|
||||||
|
# <-------- 文本碎片重组为完整的tex片段 ---------->
|
||||||
|
pfg.sp_file_result = []
|
||||||
|
for i_say, gpt_say, orig_content in zip(gpt_response_collection[0::2], gpt_response_collection[1::2], pfg.sp_file_contents):
|
||||||
|
pfg.sp_file_result.append(gpt_say)
|
||||||
|
pfg.merge_result()
|
||||||
|
|
||||||
|
# <-------- 临时存储用于调试 ---------->
|
||||||
|
pfg.get_token_num = None
|
||||||
|
objdump(pfg, file=pj(project_folder,'temp.pkl'))
|
||||||
|
|
||||||
|
|
||||||
|
# <-------- 写出文件 ---------->
|
||||||
|
msg = f"当前大语言模型: {llm_kwargs['llm_model']}，当前语言模型温度设定: {llm_kwargs['temperature']}。"
|
||||||
|
final_tex = lps.merge_result(pfg.file_result, mode, msg)
|
||||||
|
with open(project_folder + f'/merge_{mode}.tex', 'w', encoding='utf-8', errors='replace') as f:
|
||||||
|
if mode != 'translate_zh' or "binary" in final_tex: f.write(final_tex)
|
||||||
|
|
||||||
|
|
||||||
|
# <-------- 整理结果, 退出 ---------->
|
||||||
|
chatbot.append((f"完成了吗？", 'GPT结果已输出, 正在编译PDF'))
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||||
|
|
||||||
|
# <-------- 返回 ---------->
|
||||||
|
return project_folder + f'/merge_{mode}.tex'
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
def remove_buggy_lines(file_path, log_path, tex_name, tex_name_pure, n_fix, work_folder_modified):
|
||||||
|
try:
|
||||||
|
with open(log_path, 'r', encoding='utf-8', errors='replace') as f:
|
||||||
|
log = f.read()
|
||||||
|
with open(file_path, 'r', encoding='utf-8', errors='replace') as f:
|
||||||
|
file_lines = f.readlines()
|
||||||
|
import re
|
||||||
|
buggy_lines = re.findall(tex_name+':([0-9]{1,5}):', log)
|
||||||
|
buggy_lines = [int(l) for l in buggy_lines]
|
||||||
|
buggy_lines = sorted(buggy_lines)
|
||||||
|
print("removing lines that has errors", buggy_lines)
|
||||||
|
file_lines.pop(buggy_lines[0]-1)
|
||||||
|
with open(pj(work_folder_modified, f"{tex_name_pure}_fix_{n_fix}.tex"), 'w', encoding='utf-8', errors='replace') as f:
|
||||||
|
f.writelines(file_lines)
|
||||||
|
return True, f"{tex_name_pure}_fix_{n_fix}", buggy_lines
|
||||||
|
except:
|
||||||
|
print("Fatal error occurred, but we cannot identify error, please download zip, read latex log, and compile manually.")
|
||||||
|
return False, -1, [-1]
|
||||||
|
|
||||||
|
|
||||||
|
def compile_latex_with_timeout(command, timeout=60):
|
||||||
|
import subprocess
|
||||||
|
process = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||||
|
try:
|
||||||
|
stdout, stderr = process.communicate(timeout=timeout)
|
||||||
|
except subprocess.TimeoutExpired:
|
||||||
|
process.kill()
|
||||||
|
stdout, stderr = process.communicate()
|
||||||
|
print("Process timed out!")
|
||||||
|
return False
|
||||||
|
return True
|
||||||
|
|
||||||
|
def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_folder_original, work_folder_modified, work_folder):
|
||||||
|
import os, time
|
||||||
|
current_dir = os.getcwd()
|
||||||
|
n_fix = 1
|
||||||
|
max_try = 32
|
||||||
|
chatbot.append([f"正在编译PDF文档", f'编译已经开始。当前工作路径为{work_folder}，如果程序停顿5分钟以上，则大概率是卡死在Latex里面了。不幸卡死时请直接去该路径下取回翻译结果，或者重启之后再度尝试 ...']); yield from update_ui(chatbot=chatbot, history=history)
|
||||||
|
chatbot.append([f"正在编译PDF文档", '...']); yield from update_ui(chatbot=chatbot, history=history); time.sleep(1); chatbot[-1] = list(chatbot[-1]) # 刷新界面
|
||||||
|
yield from update_ui_lastest_msg('编译已经开始...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
|
||||||
|
while True:
|
||||||
|
import os
|
||||||
|
# https://stackoverflow.com/questions/738755/dont-make-me-manually-abort-a-latex-compile-when-theres-an-error
|
||||||
|
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译原始PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
|
||||||
|
|
||||||
|
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译转化后的PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||||
|
|
||||||
|
if ok and os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf')):
|
||||||
|
# 只有第二步成功，才能继续下面的步骤
|
||||||
|
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译BibTex ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
if not os.path.exists(pj(work_folder_original, f'{main_file_original}.bbl')):
|
||||||
|
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'bibtex {main_file_original}.aux'); os.chdir(current_dir)
|
||||||
|
if not os.path.exists(pj(work_folder_modified, f'{main_file_modified}.bbl')):
|
||||||
|
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'bibtex {main_file_modified}.aux'); os.chdir(current_dir)
|
||||||
|
|
||||||
|
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 编译文献交叉引用 ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
|
||||||
|
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||||
|
os.chdir(work_folder_original); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_original}.tex'); os.chdir(current_dir)
|
||||||
|
os.chdir(work_folder_modified); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error {main_file_modified}.tex'); os.chdir(current_dir)
|
||||||
|
|
||||||
|
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
print( f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
|
||||||
|
ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
|
||||||
|
|
||||||
|
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||||
|
os.chdir(work_folder); ok = compile_latex_with_timeout(f'bibtex merge_diff.aux'); os.chdir(current_dir)
|
||||||
|
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||||
|
os.chdir(work_folder); ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex'); os.chdir(current_dir)
|
||||||
|
|
||||||
|
# <--------------------->
|
||||||
|
os.chdir(current_dir)
|
||||||
|
|
||||||
|
# <---------- 检查结果 ----------->
|
||||||
|
results_ = ""
|
||||||
|
original_pdf_success = os.path.exists(pj(work_folder_original, f'{main_file_original}.pdf'))
|
||||||
|
modified_pdf_success = os.path.exists(pj(work_folder_modified, f'{main_file_modified}.pdf'))
|
||||||
|
diff_pdf_success = os.path.exists(pj(work_folder, f'merge_diff.pdf'))
|
||||||
|
results_ += f"原始PDF编译是否成功: {original_pdf_success};"
|
||||||
|
results_ += f"转化PDF编译是否成功: {modified_pdf_success};"
|
||||||
|
results_ += f"对比PDF编译是否成功: {diff_pdf_success};"
|
||||||
|
yield from update_ui_lastest_msg(f'第{n_fix}编译结束:<br/>{results_}...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
|
||||||
|
if modified_pdf_success:
|
||||||
|
yield from update_ui_lastest_msg(f'转化PDF编译已经成功, 即将退出 ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
os.chdir(current_dir)
|
||||||
|
result_pdf = pj(work_folder_modified, f'{main_file_modified}.pdf')
|
||||||
|
if os.path.exists(pj(work_folder, '..', 'translation')):
|
||||||
|
shutil.copyfile(result_pdf, pj(work_folder, '..', 'translation', 'translate_zh.pdf'))
|
||||||
|
promote_file_to_downloadzone(result_pdf)
|
||||||
|
return True # 成功啦
|
||||||
|
else:
|
||||||
|
if n_fix>=max_try: break
|
||||||
|
n_fix += 1
|
||||||
|
can_retry, main_file_modified, buggy_lines = remove_buggy_lines(
|
||||||
|
file_path=pj(work_folder_modified, f'{main_file_modified}.tex'),
|
||||||
|
log_path=pj(work_folder_modified, f'{main_file_modified}.log'),
|
||||||
|
tex_name=f'{main_file_modified}.tex',
|
||||||
|
tex_name_pure=f'{main_file_modified}',
|
||||||
|
n_fix=n_fix,
|
||||||
|
work_folder_modified=work_folder_modified,
|
||||||
|
)
|
||||||
|
yield from update_ui_lastest_msg(f'由于最为关键的转化PDF编译失败, 将根据报错信息修正tex源文件并重试, 当前报错的latex代码处于第{buggy_lines}行 ...', chatbot, history) # 刷新Gradio前端界面
|
||||||
|
if not can_retry: break
|
||||||
|
|
||||||
|
os.chdir(current_dir)
|
||||||
|
return False # 失败啦
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
@@ -99,6 +99,7 @@ services:
|
|||||||
command: >
|
command: >
|
||||||
bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
|
bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
|
||||||
git pull &&
|
git pull &&
|
||||||
|
pip install -r requirements.txt &&
|
||||||
echo '[jittorllms] 正在从github拉取最新代码...' &&
|
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 &&
|
git --git-dir=request_llm/jittorllms/.git --work-tree=request_llm/jittorllms pull --force &&
|
||||||
python3 -u main.py"
|
python3 -u main.py"
|
||||||
|
|||||||
27
docs/Dockerfile+NoLocal+Latex
普通文件
27
docs/Dockerfile+NoLocal+Latex
普通文件
@@ -0,0 +1,27 @@
|
|||||||
|
# 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM
|
||||||
|
# - 1 修改 `config.py`
|
||||||
|
# - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/Dockerfile+NoLocal+Latex .
|
||||||
|
# - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
|
||||||
|
|
||||||
|
FROM fuqingxu/python311_texlive_ctex:latest
|
||||||
|
|
||||||
|
# 指定路径
|
||||||
|
WORKDIR /gpt
|
||||||
|
|
||||||
|
ARG useProxyNetwork=''
|
||||||
|
|
||||||
|
RUN $useProxyNetwork pip3 install gradio openai numpy arxiv rich -i https://pypi.douban.com/simple/
|
||||||
|
RUN $useProxyNetwork pip3 install colorama Markdown pygments pymupdf -i https://pypi.douban.com/simple/
|
||||||
|
|
||||||
|
# 装载项目文件
|
||||||
|
COPY . .
|
||||||
|
|
||||||
|
|
||||||
|
# 安装依赖
|
||||||
|
RUN $useProxyNetwork pip3 install -r requirements.txt -i https://pypi.douban.com/simple/
|
||||||
|
|
||||||
|
# 可选步骤，用于预热模块
|
||||||
|
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
|
||||||
|
|
||||||
|
# 启动
|
||||||
|
CMD ["python3", "-u", "main.py"]
|
||||||
@@ -2,11 +2,11 @@
|
|||||||
>
|
>
|
||||||
> Durante l'installazione delle dipendenze, selezionare rigorosamente le **versioni specificate** nel file requirements.txt.
|
> Durante l'installazione delle dipendenze, selezionare rigorosamente le **versioni specificate** nel file requirements.txt.
|
||||||
>
|
>
|
||||||
> ` pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/`
|
> ` pip install -r requirements.txt`
|
||||||
|
|
||||||
# <img src="docs/logo.png" width="40" > GPT Ottimizzazione Accademica (GPT Academic)
|
# <img src="logo.png" width="40" > GPT Ottimizzazione Accademica (GPT Academic)
|
||||||
|
|
||||||
**Se ti piace questo progetto, ti preghiamo di dargli una stella. Se hai sviluppato scorciatoie accademiche o plugin funzionali più utili, non esitare ad aprire una issue o pull request. Abbiamo anche una README in [Inglese|](docs/README_EN.md)[Giapponese|](docs/README_JP.md)[Coreano|](https://github.com/mldljyh/ko_gpt_academic)[Russo|](docs/README_RS.md)[Francese](docs/README_FR.md) tradotta da questo stesso progetto.
|
**Se ti piace questo progetto, ti preghiamo di dargli una stella. Se hai sviluppato scorciatoie accademiche o plugin funzionali più utili, non esitare ad aprire una issue o pull request. Abbiamo anche una README in [Inglese|](README_EN.md)[Giapponese|](README_JP.md)[Coreano|](https://github.com/mldljyh/ko_gpt_academic)[Russo|](README_RS.md)[Francese](README_FR.md) tradotta da questo stesso progetto.
|
||||||
Per tradurre questo progetto in qualsiasi lingua con GPT, leggere e eseguire [`multi_language.py`](multi_language.py) (sperimentale).
|
Per tradurre questo progetto in qualsiasi lingua con GPT, leggere e eseguire [`multi_language.py`](multi_language.py) (sperimentale).
|
||||||
|
|
||||||
> **Nota**
|
> **Nota**
|
||||||
@@ -17,7 +17,9 @@ Per tradurre questo progetto in qualsiasi lingua con GPT, leggere e eseguire [`m
|
|||||||
>
|
>
|
||||||
> 3. Questo progetto è compatibile e incoraggia l'utilizzo di grandi modelli di linguaggio di produzione nazionale come chatglm, RWKV, Pangu ecc. Supporta la coesistenza di più api-key e può essere compilato nel file di configurazione come `API_KEY="openai-key1,openai-key2,api2d-key3"`. Per sostituire temporaneamente `API_KEY`, inserire `API_KEY` temporaneo nell'area di input e premere Invio per renderlo effettivo.
|
> 3. Questo progetto è compatibile e incoraggia l'utilizzo di grandi modelli di linguaggio di produzione nazionale come chatglm, RWKV, Pangu ecc. Supporta la coesistenza di più api-key e può essere compilato nel file di configurazione come `API_KEY="openai-key1,openai-key2,api2d-key3"`. Per sostituire temporaneamente `API_KEY`, inserire `API_KEY` temporaneo nell'area di input e premere Invio per renderlo effettivo.
|
||||||
|
|
||||||
<div align="center">Funzione | Descrizione
|
<div align="center">
|
||||||
|
|
||||||
|
Funzione | Descrizione
|
||||||
--- | ---
|
--- | ---
|
||||||
Correzione immediata | Supporta correzione immediata e ricerca degli errori di grammatica del documento con un solo clic
|
Correzione immediata | Supporta correzione immediata e ricerca degli errori di grammatica del documento con un solo clic
|
||||||
Traduzione cinese-inglese immediata | Traduzione cinese-inglese immediata con un solo clic
|
Traduzione cinese-inglese immediata | Traduzione cinese-inglese immediata con un solo clic
|
||||||
@@ -41,6 +43,8 @@ Avvia il tema di gradio [scuro](https://github.com/binary-husky/chatgpt_academic
|
|||||||
Supporto per maggiori modelli LLM, supporto API2D | Sentirsi serviti simultaneamente da GPT3.5, GPT4, [Tsinghua ChatGLM](https://github.com/THUDM/ChatGLM-6B), [Fudan MOSS](https://github.com/OpenLMLab/MOSS) deve essere una grande sensazione, giusto?
|
Supporto per maggiori modelli LLM, supporto API2D | Sentirsi serviti simultaneamente da GPT3.5, GPT4, [Tsinghua ChatGLM](https://github.com/THUDM/ChatGLM-6B), [Fudan MOSS](https://github.com/OpenLMLab/MOSS) deve essere una grande sensazione, giusto?
|
||||||
Ulteriori modelli LLM supportat,i supporto per l'implementazione di Huggingface | Aggiunta di un'interfaccia Newbing (Nuovo Bing), introdotta la compatibilità con Tsinghua [Jittorllms](https://github.com/Jittor/JittorLLMs), [LLaMA](https://github.com/facebookresearch/llama), [RWKV](https://github.com/BlinkDL/ChatRWKV) e [PanGu-α](https://openi.org.cn/pangu/)
|
Ulteriori modelli LLM supportat,i supporto per l'implementazione di Huggingface | Aggiunta di un'interfaccia Newbing (Nuovo Bing), introdotta la compatibilità con Tsinghua [Jittorllms](https://github.com/Jittor/JittorLLMs), [LLaMA](https://github.com/facebookresearch/llama), [RWKV](https://github.com/BlinkDL/ChatRWKV) e [PanGu-α](https://openi.org.cn/pangu/)
|
||||||
Ulteriori dimostrazioni di nuove funzionalità (generazione di immagini, ecc.)... | Vedere la fine di questo documento...
|
Ulteriori dimostrazioni di nuove funzionalità (generazione di immagini, ecc.)... | Vedere la fine di questo documento...
|
||||||
|
</div>
|
||||||
|
|
||||||
|
|
||||||
- Nuova interfaccia (modificare l'opzione LAYOUT in `config.py` per passare dal layout a sinistra e a destra al layout superiore e inferiore)
|
- Nuova interfaccia (modificare l'opzione LAYOUT in `config.py` per passare dal layout a sinistra e a destra al layout superiore e inferiore)
|
||||||
<div align="center">
|
<div align="center">
|
||||||
@@ -202,11 +206,13 @@ ad esempio
|
|||||||
2. Plugin di funzione personalizzati
|
2. Plugin di funzione personalizzati
|
||||||
|
|
||||||
Scrivi plugin di funzione personalizzati e esegui tutte le attività che desideri o non hai mai pensato di fare.
|
Scrivi plugin di funzione personalizzati e esegui tutte le attività che desideri o non hai mai pensato di fare.
|
||||||
La difficoltà di scrittura e debug dei plugin del nostro progetto è molto bassa. Se si dispone di una certa conoscenza di base di Python, è possibile realizzare la propria funzione del plugin seguendo il nostro modello. Per maggiori dettagli, consultare la [guida al plugin per funzioni] (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).
|
La difficoltà di scrittura e debug dei plugin del nostro progetto è molto bassa. Se si dispone di una certa conoscenza di base di Python, è possibile realizzare la propria funzione del plugin seguendo il nostro modello. Per maggiori dettagli, consultare la [guida al plugin per funzioni](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).
|
||||||
|
|
||||||
---
|
---
|
||||||
# Ultimo aggiornamento
|
# Ultimo aggiornamento
|
||||||
## Nuove funzionalità dinamiche1. Funzionalità di salvataggio della conversazione. Nell'area dei plugin della funzione, fare clic su "Salva la conversazione corrente" per salvare la conversazione corrente come file html leggibile e ripristinabile, inoltre, nell'area dei plugin della funzione (menu a discesa), fare clic su "Carica la cronologia della conversazione archiviata" per ripristinare la conversazione precedente. Suggerimento: fare clic su "Carica la cronologia della conversazione archiviata" senza specificare il file consente di visualizzare la cache degli archivi html di cronologia, fare clic su "Elimina tutti i record di cronologia delle conversazioni locali" per eliminare tutte le cache degli archivi html.
|
## Nuove funzionalità dinamiche
|
||||||
|
|
||||||
|
1. Funzionalità di salvataggio della conversazione. Nell'area dei plugin della funzione, fare clic su "Salva la conversazione corrente" per salvare la conversazione corrente come file html leggibile e ripristinabile, inoltre, nell'area dei plugin della funzione (menu a discesa), fare clic su "Carica la cronologia della conversazione archiviata" per ripristinare la conversazione precedente. Suggerimento: fare clic su "Carica la cronologia della conversazione archiviata" senza specificare il file consente di visualizzare la cache degli archivi html di cronologia, fare clic su "Elimina tutti i record di cronologia delle conversazioni locali" per eliminare tutte le cache degli archivi html.
|
||||||
<div align="center">
|
<div align="center">
|
||||||
<img src="https://user-images.githubusercontent.com/96192199/235222390-24a9acc0-680f-49f5-bc81-2f3161f1e049.png" width="500" >
|
<img src="https://user-images.githubusercontent.com/96192199/235222390-24a9acc0-680f-49f5-bc81-2f3161f1e049.png" width="500" >
|
||||||
</div>
|
</div>
|
||||||
@@ -307,4 +313,4 @@ https://github.com/kaixindelele/ChatPaper
|
|||||||
# Altro:
|
# Altro:
|
||||||
https://github.com/gradio-app/gradio
|
https://github.com/gradio-app/gradio
|
||||||
https://github.com/fghrsh/live2d_demo
|
https://github.com/fghrsh/live2d_demo
|
||||||
```
|
```
|
||||||
|
|||||||
@@ -17,7 +17,9 @@ GPT를 이용하여 프로젝트를 임의의 언어로 번역하려면 [`multi_
|
|||||||
>
|
>
|
||||||
> 3. 이 프로젝트는 국내 언어 모델 chatglm과 RWKV, 판고 등의 시도와 호환 가능합니다. 여러 개의 api-key를 지원하며 설정 파일에 "API_KEY="openai-key1,openai-key2,api2d-key3""와 같이 작성할 수 있습니다. `API_KEY`를 임시로 변경해야하는 경우 입력 영역에 임시 `API_KEY`를 입력 한 후 엔터 키를 누르면 즉시 적용됩니다.
|
> 3. 이 프로젝트는 국내 언어 모델 chatglm과 RWKV, 판고 등의 시도와 호환 가능합니다. 여러 개의 api-key를 지원하며 설정 파일에 "API_KEY="openai-key1,openai-key2,api2d-key3""와 같이 작성할 수 있습니다. `API_KEY`를 임시로 변경해야하는 경우 입력 영역에 임시 `API_KEY`를 입력 한 후 엔터 키를 누르면 즉시 적용됩니다.
|
||||||
|
|
||||||
<div align="center">기능 | 설명
|
<div align="center">
|
||||||
|
|
||||||
|
기능 | 설명
|
||||||
--- | ---
|
--- | ---
|
||||||
원 키워드 | 원 키워드 및 논문 문법 오류를 찾는 기능 지원
|
원 키워드 | 원 키워드 및 논문 문법 오류를 찾는 기능 지원
|
||||||
한-영 키워드 | 한-영 키워드 지원
|
한-영 키워드 | 한-영 키워드 지원
|
||||||
@@ -265,4 +267,4 @@ https://github.com/kaixindelele/ChatPaper
|
|||||||
# 더 많은 :
|
# 더 많은 :
|
||||||
https://github.com/gradio-app/gradio
|
https://github.com/gradio-app/gradio
|
||||||
https://github.com/fghrsh/live2d_demo
|
https://github.com/fghrsh/live2d_demo
|
||||||
```
|
```
|
||||||
|
|||||||
@@ -2,7 +2,7 @@
|
|||||||
>
|
>
|
||||||
> Ao instalar as dependências, por favor, selecione rigorosamente as versões **especificadas** no arquivo requirements.txt.
|
> Ao instalar as dependências, por favor, selecione rigorosamente as versões **especificadas** no arquivo requirements.txt.
|
||||||
>
|
>
|
||||||
> `pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/`
|
> `pip install -r requirements.txt`
|
||||||
>
|
>
|
||||||
|
|
||||||
# <img src="logo.png" width="40" > Otimização acadêmica GPT (GPT Academic)
|
# <img src="logo.png" width="40" > Otimização acadêmica GPT (GPT Academic)
|
||||||
@@ -18,7 +18,9 @@ Para traduzir este projeto para qualquer idioma com o GPT, leia e execute [`mult
|
|||||||
>
|
>
|
||||||
> 3. Este projeto é compatível com e incentiva o uso de modelos de linguagem nacionais, como chatglm e RWKV, Pangolin, etc. Suporta a coexistência de várias chaves de API e pode ser preenchido no arquivo de configuração como `API_KEY="openai-key1,openai-key2,api2d-key3"`. Quando precisar alterar temporariamente o `API_KEY`, basta digitar o `API_KEY` temporário na área de entrada e pressionar Enter para que ele entre em vigor.
|
> 3. Este projeto é compatível com e incentiva o uso de modelos de linguagem nacionais, como chatglm e RWKV, Pangolin, etc. Suporta a coexistência de várias chaves de API e pode ser preenchido no arquivo de configuração como `API_KEY="openai-key1,openai-key2,api2d-key3"`. Quando precisar alterar temporariamente o `API_KEY`, basta digitar o `API_KEY` temporário na área de entrada e pressionar Enter para que ele entre em vigor.
|
||||||
|
|
||||||
<div align="center">Funcionalidade | Descrição
|
<div align="center">
|
||||||
|
|
||||||
|
Funcionalidade | Descrição
|
||||||
--- | ---
|
--- | ---
|
||||||
Um clique de polimento | Suporte a um clique polimento, um clique encontrar erros de gramática no artigo
|
Um clique de polimento | Suporte a um clique polimento, um clique encontrar erros de gramática no artigo
|
||||||
Tradução chinês-inglês de um clique | Tradução chinês-inglês de um clique
|
Tradução chinês-inglês de um clique | Tradução chinês-inglês de um clique
|
||||||
@@ -216,7 +218,9 @@ Para mais detalhes, consulte o [Guia do plug-in de função.](https://github.com
|
|||||||
|
|
||||||
---
|
---
|
||||||
# Última atualização
|
# Última atualização
|
||||||
## Novas funções dinâmicas.1. Função de salvamento de diálogo. Ao chamar o plug-in de função "Salvar diálogo atual", é possível salvar o diálogo atual em um arquivo html legível e reversível. Além disso, ao chamar o plug-in de função "Carregar arquivo de histórico de diálogo" no menu suspenso da área de plug-in, é possível restaurar uma conversa anterior. Dica: clicar em "Carregar arquivo de histórico de diálogo" sem especificar um arquivo permite visualizar o cache do arquivo html de histórico. Clicar em "Excluir todo o registro de histórico de diálogo local" permite excluir todo o cache de arquivo html.
|
## Novas funções dinâmicas.
|
||||||
|
|
||||||
|
1. Função de salvamento de diálogo. Ao chamar o plug-in de função "Salvar diálogo atual", é possível salvar o diálogo atual em um arquivo html legível e reversível. Além disso, ao chamar o plug-in de função "Carregar arquivo de histórico de diálogo" no menu suspenso da área de plug-in, é possível restaurar uma conversa anterior. Dica: clicar em "Carregar arquivo de histórico de diálogo" sem especificar um arquivo permite visualizar o cache do arquivo html de histórico. Clicar em "Excluir todo o registro de histórico de diálogo local" permite excluir todo o cache de arquivo html.
|
||||||
<div align="center">
|
<div align="center">
|
||||||
<img src="https://user-images.githubusercontent.com/96192199/235222390-24a9acc0-680f-49f5-bc81-2f3161f1e049.png" width="500" >
|
<img src="https://user-images.githubusercontent.com/96192199/235222390-24a9acc0-680f-49f5-bc81-2f3161f1e049.png" width="500" >
|
||||||
</div>
|
</div>
|
||||||
@@ -317,4 +321,4 @@ https://github.com/kaixindelele/ChatPaper
|
|||||||
# Mais:
|
# Mais:
|
||||||
https://github.com/gradio-app/gradio
|
https://github.com/gradio-app/gradio
|
||||||
https://github.com/fghrsh/live2d_demo
|
https://github.com/fghrsh/live2d_demo
|
||||||
```
|
```
|
||||||
|
|||||||
二进制文件未显示。
10
main.py
10
main.py
@@ -2,7 +2,7 @@ import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
|
|||||||
|
|
||||||
def main():
|
def main():
|
||||||
import gradio as gr
|
import gradio as gr
|
||||||
if gr.__version__ not in ['3.28.3','3.32.2']: assert False, "请用 pip install -r requirements.txt 安装依赖"
|
if gr.__version__ not in ['3.28.3','3.32.2']: assert False, "需要特殊依赖，请务必用 pip install -r requirements.txt 指令安装依赖，详情信息见requirements.txt"
|
||||||
from request_llm.bridge_all import predict
|
from request_llm.bridge_all import predict
|
||||||
from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
|
from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith
|
||||||
# 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
|
# 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
|
||||||
@@ -197,7 +197,10 @@ def main():
|
|||||||
threading.Thread(target=warm_up_modules, name="warm-up", daemon=True).start()
|
threading.Thread(target=warm_up_modules, name="warm-up", daemon=True).start()
|
||||||
|
|
||||||
auto_opentab_delay()
|
auto_opentab_delay()
|
||||||
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
|
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
|
||||||
|
server_name="0.0.0.0", server_port=PORT,
|
||||||
|
favicon_path="docs/logo.png", auth=AUTHENTICATION,
|
||||||
|
blocked_paths=["config.py","config_private.py","docker-compose.yml","Dockerfile"])
|
||||||
|
|
||||||
# 如果需要在二级路径下运行
|
# 如果需要在二级路径下运行
|
||||||
# CUSTOM_PATH, = get_conf('CUSTOM_PATH')
|
# CUSTOM_PATH, = get_conf('CUSTOM_PATH')
|
||||||
@@ -205,7 +208,8 @@ def main():
|
|||||||
# from toolbox import run_gradio_in_subpath
|
# from toolbox import run_gradio_in_subpath
|
||||||
# run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH)
|
# run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH)
|
||||||
# else:
|
# else:
|
||||||
# demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png")
|
# demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png",
|
||||||
|
# blocked_paths=["config.py","config_private.py","docker-compose.yml","Dockerfile"])
|
||||||
|
|
||||||
if __name__ == "__main__":
|
if __name__ == "__main__":
|
||||||
main()
|
main()
|
||||||
|
|||||||
@@ -15,4 +15,4 @@ pymupdf
|
|||||||
openai
|
openai
|
||||||
numpy
|
numpy
|
||||||
arxiv
|
arxiv
|
||||||
rich
|
rich
|
||||||
51
toolbox.py
51
toolbox.py
@@ -1,6 +1,6 @@
|
|||||||
import markdown
|
import markdown
|
||||||
import importlib
|
import importlib
|
||||||
import traceback
|
import time
|
||||||
import inspect
|
import inspect
|
||||||
import re
|
import re
|
||||||
import os
|
import os
|
||||||
@@ -70,6 +70,17 @@ def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
|
|||||||
assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时，可用clear将其清空，然后用for+append循环重新赋值。"
|
assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时，可用clear将其清空，然后用for+append循环重新赋值。"
|
||||||
yield chatbot.get_cookies(), chatbot, history, msg
|
yield chatbot.get_cookies(), chatbot, history, msg
|
||||||
|
|
||||||
|
def update_ui_lastest_msg(lastmsg, chatbot, history, delay=1): # 刷新界面
|
||||||
|
"""
|
||||||
|
刷新用户界面
|
||||||
|
"""
|
||||||
|
if len(chatbot) == 0: chatbot.append(["update_ui_last_msg", lastmsg])
|
||||||
|
chatbot[-1] = list(chatbot[-1])
|
||||||
|
chatbot[-1][-1] = lastmsg
|
||||||
|
yield from update_ui(chatbot=chatbot, history=history)
|
||||||
|
time.sleep(delay)
|
||||||
|
|
||||||
|
|
||||||
def trimmed_format_exc():
|
def trimmed_format_exc():
|
||||||
import os, traceback
|
import os, traceback
|
||||||
str = traceback.format_exc()
|
str = traceback.format_exc()
|
||||||
@@ -83,7 +94,7 @@ def CatchException(f):
|
|||||||
"""
|
"""
|
||||||
|
|
||||||
@wraps(f)
|
@wraps(f)
|
||||||
def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT=-1):
|
||||||
try:
|
try:
|
||||||
yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
|
yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
@@ -420,6 +431,13 @@ def find_recent_files(directory):
|
|||||||
|
|
||||||
return recent_files
|
return recent_files
|
||||||
|
|
||||||
|
def promote_file_to_downloadzone(file, rename_file=None):
|
||||||
|
# 将文件复制一份到下载区
|
||||||
|
import shutil
|
||||||
|
if rename_file is None: rename_file = f'{gen_time_str()}-{os.path.basename(file)}'
|
||||||
|
new_path = os.path.join(f'./gpt_log/', rename_file)
|
||||||
|
if os.path.exists(new_path): os.remove(new_path)
|
||||||
|
shutil.copyfile(file, new_path)
|
||||||
|
|
||||||
def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
|
def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
|
||||||
"""
|
"""
|
||||||
@@ -728,6 +746,8 @@ def clip_history(inputs, history, tokenizer, max_token_limit):
|
|||||||
其他小工具:
|
其他小工具:
|
||||||
- zip_folder: 把某个路径下所有文件压缩，然后转移到指定的另一个路径中（gpt写的）
|
- zip_folder: 把某个路径下所有文件压缩，然后转移到指定的另一个路径中（gpt写的）
|
||||||
- gen_time_str: 生成时间戳
|
- gen_time_str: 生成时间戳
|
||||||
|
- ProxyNetworkActivate: 临时地启动代理网络（如果有）
|
||||||
|
- objdump/objload: 快捷的调试函数
|
||||||
========================================================================
|
========================================================================
|
||||||
"""
|
"""
|
||||||
|
|
||||||
@@ -762,11 +782,15 @@ def zip_folder(source_folder, dest_folder, zip_name):
|
|||||||
|
|
||||||
print(f"Zip file created at {zip_file}")
|
print(f"Zip file created at {zip_file}")
|
||||||
|
|
||||||
|
def zip_result(folder):
|
||||||
|
import time
|
||||||
|
t = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
|
||||||
|
zip_folder(folder, './gpt_log/', f'{t}-result.zip')
|
||||||
|
|
||||||
def gen_time_str():
|
def gen_time_str():
|
||||||
import time
|
import time
|
||||||
return time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
|
return time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
|
||||||
|
|
||||||
|
|
||||||
class ProxyNetworkActivate():
|
class ProxyNetworkActivate():
|
||||||
"""
|
"""
|
||||||
这段代码定义了一个名为TempProxy的空上下文管理器, 用于给一小段代码上代理
|
这段代码定义了一个名为TempProxy的空上下文管理器, 用于给一小段代码上代理
|
||||||
@@ -775,12 +799,27 @@ class ProxyNetworkActivate():
|
|||||||
from toolbox import get_conf
|
from toolbox import get_conf
|
||||||
proxies, = get_conf('proxies')
|
proxies, = get_conf('proxies')
|
||||||
if 'no_proxy' in os.environ: os.environ.pop('no_proxy')
|
if 'no_proxy' in os.environ: os.environ.pop('no_proxy')
|
||||||
os.environ['HTTP_PROXY'] = proxies['http']
|
if proxies is not None:
|
||||||
os.environ['HTTPS_PROXY'] = proxies['https']
|
if 'http' in proxies: os.environ['HTTP_PROXY'] = proxies['http']
|
||||||
|
if 'https' in proxies: os.environ['HTTPS_PROXY'] = proxies['https']
|
||||||
return self
|
return self
|
||||||
|
|
||||||
def __exit__(self, exc_type, exc_value, traceback):
|
def __exit__(self, exc_type, exc_value, traceback):
|
||||||
os.environ['no_proxy'] = '*'
|
os.environ['no_proxy'] = '*'
|
||||||
if 'HTTP_PROXY' in os.environ: os.environ.pop('HTTP_PROXY')
|
if 'HTTP_PROXY' in os.environ: os.environ.pop('HTTP_PROXY')
|
||||||
if 'HTTPS_PROXY' in os.environ: os.environ.pop('HTTPS_PROXY')
|
if 'HTTPS_PROXY' in os.environ: os.environ.pop('HTTPS_PROXY')
|
||||||
return
|
return
|
||||||
|
|
||||||
|
def objdump(obj, file='objdump.tmp'):
|
||||||
|
import pickle
|
||||||
|
with open(file, 'wb+') as f:
|
||||||
|
pickle.dump(obj, f)
|
||||||
|
return
|
||||||
|
|
||||||
|
def objload(file='objdump.tmp'):
|
||||||
|
import pickle, os
|
||||||
|
if not os.path.exists(file):
|
||||||
|
return
|
||||||
|
with open(file, 'rb') as f:
|
||||||
|
return pickle.load(f)
|
||||||
|
|
||||||
4
version
4
version
@@ -1,5 +1,5 @@
|
|||||||
{
|
{
|
||||||
"version": 3.37,
|
"version": 3.4,
|
||||||
"show_feature": true,
|
"show_feature": true,
|
||||||
"new_feature": "修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件 <-> 添加了OpenAI音频转文本总结插件 <-> 通过Slack添加对Claude的支持 <-> 提供复旦MOSS模型适配（启用需额外依赖） <-> 提供docker-compose方案兼容LLAMA盘古RWKV等模型的后端 <-> 新增Live2D装饰 <-> 完善对话历史的保存/载入/删除 <-> 保存对话功能"
|
"new_feature": "新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件 <-> 添加了OpenAI音频转文本总结插件 <-> 通过Slack添加对Claude的支持"
|
||||||
}
|
}
|
||||||
|
|||||||
在新工单中引用
屏蔽一个用户