Merge branch 'master' into jsz14897502-master
This commit is contained in:
commit
a0f592308a
44
.github/workflows/build-with-all-capacity.yml
vendored
Normal file
44
.github/workflows/build-with-all-capacity.yml
vendored
Normal file
@ -0,0 +1,44 @@
|
||||
# https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages
|
||||
name: build-with-all-capacity
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- 'master'
|
||||
|
||||
env:
|
||||
REGISTRY: ghcr.io
|
||||
IMAGE_NAME: ${{ github.repository }}_with_all_capacity
|
||||
|
||||
jobs:
|
||||
build-and-push-image:
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
packages: write
|
||||
|
||||
steps:
|
||||
- name: Checkout repository
|
||||
uses: actions/checkout@v3
|
||||
|
||||
- name: Log in to the Container registry
|
||||
uses: docker/login-action@v2
|
||||
with:
|
||||
registry: ${{ env.REGISTRY }}
|
||||
username: ${{ github.actor }}
|
||||
password: ${{ secrets.GITHUB_TOKEN }}
|
||||
|
||||
- name: Extract metadata (tags, labels) for Docker
|
||||
id: meta
|
||||
uses: docker/metadata-action@v4
|
||||
with:
|
||||
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
|
||||
|
||||
- name: Build and push Docker image
|
||||
uses: docker/build-push-action@v4
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
file: docs/GithubAction+AllCapacity
|
||||
tags: ${{ steps.meta.outputs.tags }}
|
||||
labels: ${{ steps.meta.outputs.labels }}
|
25
.github/workflows/stale.yml
vendored
Normal file
25
.github/workflows/stale.yml
vendored
Normal file
@ -0,0 +1,25 @@
|
||||
# This workflow warns and then closes issues and PRs that have had no activity for a specified amount of time.
|
||||
#
|
||||
# You can adjust the behavior by modifying this file.
|
||||
# For more information, see:
|
||||
# https://github.com/actions/stale
|
||||
|
||||
name: 'Close stale issues and PRs'
|
||||
on:
|
||||
schedule:
|
||||
- cron: '*/5 * * * *'
|
||||
|
||||
jobs:
|
||||
stale:
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
issues: write
|
||||
pull-requests: read
|
||||
|
||||
steps:
|
||||
- uses: actions/stale@v8
|
||||
with:
|
||||
stale-issue-message: 'This issue is stale because it has been open 100 days with no activity. Remove stale label or comment or this will be closed in 1 days.'
|
||||
days-before-stale: 100
|
||||
days-before-close: 1
|
||||
debug-only: true
|
25
README.md
25
README.md
@ -10,13 +10,13 @@
|
||||
**如果喜欢这个项目,请给它一个Star;如果您发明了好用的快捷键或函数插件,欢迎发pull requests!**
|
||||
|
||||
If you like this project, please give it a Star. If you've come up with more useful academic shortcuts or functional plugins, feel free to open an issue or pull request. We also have a README in [English|](docs/README_EN.md)[日本語|](docs/README_JP.md)[한국어|](https://github.com/mldljyh/ko_gpt_academic)[Русский|](docs/README_RS.md)[Français](docs/README_FR.md) translated by this project itself.
|
||||
To translate this project to arbitary language with GPT, read and run [`multi_language.py`](multi_language.py) (experimental).
|
||||
To translate this project to arbitrary language with GPT, read and run [`multi_language.py`](multi_language.py) (experimental).
|
||||
|
||||
> **Note**
|
||||
>
|
||||
> 1.请注意只有 **高亮(如红色)** 标识的函数插件(按钮)才支持读取文件,部分插件位于插件区的**下拉菜单**中。另外我们以**最高优先级**欢迎和处理任何新插件的PR。
|
||||
> 1.请注意只有 **高亮** 标识的函数插件(按钮)才支持读取文件,部分插件位于插件区的**下拉菜单**中。另外我们以**最高优先级**欢迎和处理任何新插件的PR。
|
||||
>
|
||||
> 2.本项目中每个文件的功能都在[自译解报告`self_analysis.md`](https://github.com/binary-husky/gpt_academic/wiki/GPT‐Academic项目自译解报告)详细说明。随着版本的迭代,您也可以随时自行点击相关函数插件,调用GPT重新生成项目的自我解析报告。常见问题汇总在[`wiki`](https://github.com/binary-husky/gpt_academic/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98)当中。[安装方法](#installation)。
|
||||
> 2.本项目中每个文件的功能都在[自译解报告`self_analysis.md`](https://github.com/binary-husky/gpt_academic/wiki/GPT‐Academic项目自译解报告)详细说明。随着版本的迭代,您也可以随时自行点击相关函数插件,调用GPT重新生成项目的自我解析报告。常见问题[`wiki`](https://github.com/binary-husky/gpt_academic/wiki)。[安装方法](#installation) | [配置说明](https://github.com/binary-husky/gpt_academic/wiki/%E9%A1%B9%E7%9B%AE%E9%85%8D%E7%BD%AE%E8%AF%B4%E6%98%8E)。
|
||||
>
|
||||
> 3.本项目兼容并鼓励尝试国产大语言模型ChatGLM和Moss等等。支持多个api-key共存,可在配置文件中填写如`API_KEY="openai-key1,openai-key2,azure-key3,api2d-key4"`。需要临时更换`API_KEY`时,在输入区输入临时的`API_KEY`然后回车键提交后即可生效。
|
||||
|
||||
@ -53,7 +53,8 @@ Latex论文一键校对 | [函数插件] 仿Grammarly对Latex文章进行语法
|
||||
[多LLM模型](https://www.bilibili.com/video/BV1wT411p7yf)支持 | 同时被GPT3.5、GPT4、[清华ChatGLM2](https://github.com/THUDM/ChatGLM2-6B)、[复旦MOSS](https://github.com/OpenLMLab/MOSS)同时伺候的感觉一定会很不错吧?
|
||||
⭐ChatGLM2微调模型 | 支持加载ChatGLM2微调模型,提供ChatGLM2微调辅助插件
|
||||
更多LLM模型接入,支持[huggingface部署](https://huggingface.co/spaces/qingxu98/gpt-academic) | 加入Newbing接口(新必应),引入清华[Jittorllms](https://github.com/Jittor/JittorLLMs)支持[LLaMA](https://github.com/facebookresearch/llama)和[盘古α](https://openi.org.cn/pangu/)
|
||||
⭐[虚空终端](https://github.com/binary-husky/void-terminal)pip包 | 脱离GUI,在Python中直接调用本项目的函数插件(开发中)
|
||||
⭐[void-terminal](https://github.com/binary-husky/void-terminal) pip包 | 脱离GUI,在Python中直接调用本项目的所有函数插件(开发中)
|
||||
⭐虚空终端插件 | [函数插件] 用自然语言,直接调度本项目其他插件
|
||||
更多新功能展示 (图像生成等) …… | 见本文档结尾处 ……
|
||||
</div>
|
||||
|
||||
@ -148,11 +149,14 @@ python main.py
|
||||
|
||||
### 安装方法II:使用Docker
|
||||
|
||||
[](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml)
|
||||
|
||||
1. 仅ChatGPT(推荐大多数人选择,等价于docker-compose方案1)
|
||||
[](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml)
|
||||
[](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml)
|
||||
[](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml)
|
||||
|
||||
|
||||
``` sh
|
||||
git clone --depth=1 https://github.com/binary-husky/gpt_academic.git # 下载项目
|
||||
cd gpt_academic # 进入路径
|
||||
@ -249,10 +253,13 @@ Tip:不指定文件直接点击 `载入对话历史存档` 可以查看历史h
|
||||
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/9fdcc391-f823-464f-9322-f8719677043b" height="250" >
|
||||
</div>
|
||||
|
||||
3. 生成报告。大部分插件都会在执行结束后,生成工作报告
|
||||
3. 虚空终端(从自然语言输入中,理解用户意图+自动调用其他插件)
|
||||
|
||||
- 步骤一:输入 “ 请调用插件翻译PDF论文,地址为https://storage.googleapis.com/deepmind-media/alphago/AlphaGoNaturePaper.pdf ”
|
||||
- 步骤二:点击“虚空终端”
|
||||
|
||||
<div align="center">
|
||||
<img src="https://user-images.githubusercontent.com/96192199/227503770-fe29ce2c-53fd-47b0-b0ff-93805f0c2ff4.png" height="250" >
|
||||
<img src="https://user-images.githubusercontent.com/96192199/227504617-7a497bb3-0a2a-4b50-9a8a-95ae60ea7afd.png" height="250" >
|
||||
<img src="https://github.com/binary-husky/gpt_academic/assets/96192199/66f1b044-e9ff-4eed-9126-5d4f3668f1ed" width="500" >
|
||||
</div>
|
||||
|
||||
4. 模块化功能设计,简单的接口却能支持强大的功能
|
||||
@ -299,8 +306,10 @@ 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
|
||||
</div>
|
||||
|
||||
|
||||
|
||||
### II: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 3.60(todo): 优化虚空终端,引入code interpreter和更多插件
|
||||
- version 3.50: 使用自然语言调用本项目的所有函数插件(虚空终端),支持插件分类,改进UI,设计新主题
|
||||
- version 3.49: 支持百度千帆平台和文心一言
|
||||
- version 3.48: 支持阿里达摩院通义千问,上海AI-Lab书生,讯飞星火
|
||||
- version 3.46: 支持完全脱手操作的实时语音对话
|
||||
|
@ -5,7 +5,7 @@ def check_proxy(proxies):
|
||||
try:
|
||||
response = requests.get("https://ipapi.co/json/", proxies=proxies, timeout=4)
|
||||
data = response.json()
|
||||
print(f'查询代理的地理位置,返回的结果是{data}')
|
||||
# print(f'查询代理的地理位置,返回的结果是{data}')
|
||||
if 'country_name' in data:
|
||||
country = data['country_name']
|
||||
result = f"代理配置 {proxies_https}, 代理所在地:{country}"
|
||||
|
28
config.py
28
config.py
@ -43,7 +43,11 @@ API_URL_REDIRECT = {}
|
||||
DEFAULT_WORKER_NUM = 3
|
||||
|
||||
|
||||
# 对话窗的高度
|
||||
# 色彩主题,可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
|
||||
THEME = "Default"
|
||||
|
||||
|
||||
# 对话窗的高度 (仅在LAYOUT="TOP-DOWN"时生效)
|
||||
CHATBOT_HEIGHT = 1115
|
||||
|
||||
|
||||
@ -68,6 +72,10 @@ WEB_PORT = -1
|
||||
MAX_RETRY = 2
|
||||
|
||||
|
||||
# 插件分类默认选项
|
||||
DEFAULT_FN_GROUPS = ['对话', '编程', '学术']
|
||||
|
||||
|
||||
# 模型选择是 (注意: LLM_MODEL是默认选中的模型, 它*必须*被包含在AVAIL_LLM_MODELS列表中 )
|
||||
LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
|
||||
AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo",
|
||||
@ -83,7 +91,7 @@ BAIDU_CLOUD_QIANFAN_MODEL = 'ERNIE-Bot' # 可选 "ERNIE-Bot"(文心一言), "
|
||||
|
||||
|
||||
# 如果使用ChatGLM2微调模型,请把 LLM_MODEL="chatglmft",并在此处指定模型路径
|
||||
ChatGLM_PTUNING_CHECKPOINT = "" # 例如"/home/hmp/ChatGLM2-6B/ptuning/output/6b-pt-128-1e-2/checkpoint-100"
|
||||
CHATGLM_PTUNING_CHECKPOINT = "" # 例如"/home/hmp/ChatGLM2-6B/ptuning/output/6b-pt-128-1e-2/checkpoint-100"
|
||||
|
||||
|
||||
# 本地LLM模型如ChatGLM的执行方式 CPU/GPU
|
||||
@ -99,10 +107,6 @@ CONCURRENT_COUNT = 100
|
||||
AUTO_CLEAR_TXT = False
|
||||
|
||||
|
||||
# 色彩主体,可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
|
||||
THEME = "Default"
|
||||
|
||||
|
||||
# 加一个live2d装饰
|
||||
ADD_WAIFU = False
|
||||
|
||||
@ -213,6 +217,18 @@ ALLOW_RESET_CONFIG = False
|
||||
├── NEWBING_STYLE
|
||||
└── NEWBING_COOKIES
|
||||
|
||||
|
||||
用户图形界面布局依赖关系示意图
|
||||
│
|
||||
├── CHATBOT_HEIGHT 对话窗的高度
|
||||
├── CODE_HIGHLIGHT 代码高亮
|
||||
├── LAYOUT 窗口布局
|
||||
├── DARK_MODE 暗色模式 / 亮色模式
|
||||
├── DEFAULT_FN_GROUPS 插件分类默认选项
|
||||
├── THEME 色彩主题
|
||||
├── AUTO_CLEAR_TXT 是否在提交时自动清空输入框
|
||||
├── ADD_WAIFU 加一个live2d装饰
|
||||
├── ALLOW_RESET_CONFIG 是否允许通过自然语言描述修改本页的配置,该功能具有一定的危险性
|
||||
|
||||
|
||||
插件在线服务配置依赖关系示意图
|
||||
|
@ -63,6 +63,7 @@ def get_core_functions():
|
||||
"英译中": {
|
||||
"Prefix": r"翻译成地道的中文:" + "\n\n",
|
||||
"Suffix": r"",
|
||||
"Visible": False,
|
||||
},
|
||||
"找图片": {
|
||||
"Prefix": r"我需要你找一张网络图片。使用Unsplash API(https://source.unsplash.com/960x640/?<英语关键词>)获取图片URL," +
|
||||
@ -78,6 +79,7 @@ def get_core_functions():
|
||||
"Prefix": r"Here are some bibliography items, please transform them into bibtex style." +
|
||||
r"Note that, reference styles maybe more than one kind, you should transform each item correctly." +
|
||||
r"Items need to be transformed:",
|
||||
"Visible": False,
|
||||
"Suffix": r"",
|
||||
}
|
||||
}
|
||||
|
@ -34,87 +34,108 @@ def get_crazy_functions():
|
||||
from crazy_functions.Latex全文翻译 import Latex中译英
|
||||
from crazy_functions.Latex全文翻译 import Latex英译中
|
||||
from crazy_functions.批量Markdown翻译 import Markdown中译英
|
||||
from crazy_functions.虚空终端 import 虚空终端
|
||||
|
||||
|
||||
function_plugins = {
|
||||
"虚空终端": {
|
||||
"Group": "对话|编程|学术",
|
||||
"Color": "stop",
|
||||
"AsButton": True,
|
||||
"Function": HotReload(虚空终端)
|
||||
},
|
||||
"解析整个Python项目": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": True,
|
||||
"Info": "解析一个Python项目的所有源文件(.py) | 输入参数为路径",
|
||||
"Function": HotReload(解析一个Python项目)
|
||||
},
|
||||
"载入对话历史存档(先上传存档或输入路径)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"Info": "载入对话历史存档 | 输入参数为路径",
|
||||
"Function": HotReload(载入对话历史存档)
|
||||
},
|
||||
"删除所有本地对话历史记录(谨慎操作)": {
|
||||
"Group": "对话",
|
||||
"AsButton": False,
|
||||
"Info": "删除所有本地对话历史记录,谨慎操作 | 不需要输入参数",
|
||||
"Function": HotReload(删除所有本地对话历史记录)
|
||||
},
|
||||
"清除所有缓存文件(谨慎操作)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "清除所有缓存文件,谨慎操作 | 不需要输入参数",
|
||||
"Function": HotReload(清除缓存)
|
||||
},
|
||||
"批量总结Word文档": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": True,
|
||||
"Info": "批量总结word文档 | 输入参数为路径",
|
||||
"Function": HotReload(总结word文档)
|
||||
},
|
||||
"解析整个C++项目头文件": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "解析一个C++项目的所有头文件(.h/.hpp) | 输入参数为路径",
|
||||
"Function": HotReload(解析一个C项目的头文件)
|
||||
},
|
||||
"解析整个C++项目(.cpp/.hpp/.c/.h)": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "解析一个C++项目的所有源文件(.cpp/.hpp/.c/.h)| 输入参数为路径",
|
||||
"Function": HotReload(解析一个C项目)
|
||||
},
|
||||
"解析整个Go项目": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "解析一个Go项目的所有源文件 | 输入参数为路径",
|
||||
"Function": HotReload(解析一个Golang项目)
|
||||
},
|
||||
"解析整个Rust项目": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "解析一个Rust项目的所有源文件 | 输入参数为路径",
|
||||
"Function": HotReload(解析一个Rust项目)
|
||||
},
|
||||
"解析整个Java项目": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "解析一个Java项目的所有源文件 | 输入参数为路径",
|
||||
"Function": HotReload(解析一个Java项目)
|
||||
},
|
||||
"解析整个前端项目(js,ts,css等)": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "解析一个前端项目的所有源文件(js,ts,css等) | 输入参数为路径",
|
||||
"Function": HotReload(解析一个前端项目)
|
||||
},
|
||||
"解析整个Lua项目": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "解析一个Lua项目的所有源文件 | 输入参数为路径",
|
||||
"Function": HotReload(解析一个Lua项目)
|
||||
},
|
||||
"解析整个CSharp项目": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "解析一个CSharp项目的所有源文件 | 输入参数为路径",
|
||||
"Function": HotReload(解析一个CSharp项目)
|
||||
},
|
||||
"解析Jupyter Notebook文件": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"Info": "解析Jupyter Notebook文件 | 输入参数为路径",
|
||||
@ -123,92 +144,125 @@ def get_crazy_functions():
|
||||
"ArgsReminder": "若输入0,则不解析notebook中的Markdown块", # 高级参数输入区的显示提示
|
||||
},
|
||||
"读Tex论文写摘要": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": True,
|
||||
"AsButton": False,
|
||||
"Info": "读取Tex论文并写摘要 | 输入参数为路径",
|
||||
"Function": HotReload(读文章写摘要)
|
||||
},
|
||||
"翻译README或.MD": {
|
||||
"翻译README或MD": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": True,
|
||||
"Info": "将Markdown翻译为中文 | 输入参数为路径或URL",
|
||||
"Function": HotReload(Markdown英译中)
|
||||
},
|
||||
"翻译Markdown或README(支持Github链接)": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"Info": "将Markdown或README翻译为中文 | 输入参数为路径或URL",
|
||||
"Function": HotReload(Markdown英译中)
|
||||
},
|
||||
"批量生成函数注释": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "批量生成函数的注释 | 输入参数为路径",
|
||||
"Function": HotReload(批量生成函数注释)
|
||||
},
|
||||
"保存当前的对话": {
|
||||
"Group": "对话",
|
||||
"AsButton": True,
|
||||
"Info": "保存当前的对话 | 不需要输入参数",
|
||||
"Function": HotReload(对话历史存档)
|
||||
},
|
||||
"[多线程Demo] 解析此项目本身(源码自译解)": {
|
||||
"[多线程Demo]解析此项目本身(源码自译解)": {
|
||||
"Group": "对话|编程",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "多线程解析并翻译此项目的源码 | 不需要输入参数",
|
||||
"Function": HotReload(解析项目本身)
|
||||
},
|
||||
"[插件demo] 历史上的今天": {
|
||||
"[插件demo]历史上的今天": {
|
||||
"Group": "对话",
|
||||
"AsButton": True,
|
||||
"Info": "查看历史上的今天事件 | 不需要输入参数",
|
||||
"Function": HotReload(高阶功能模板函数)
|
||||
},
|
||||
"精准翻译PDF论文": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": True, # 加入下拉菜单中
|
||||
"AsButton": True,
|
||||
"Info": "精准翻译PDF论文为中文 | 输入参数为路径",
|
||||
"Function": HotReload(批量翻译PDF文档)
|
||||
},
|
||||
"询问多个GPT模型": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": True,
|
||||
"Function": HotReload(同时问询)
|
||||
},
|
||||
"批量总结PDF文档": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "批量总结PDF文档的内容 | 输入参数为路径",
|
||||
"Function": HotReload(批量总结PDF文档)
|
||||
},
|
||||
"谷歌学术检索助手(输入谷歌学术搜索页url)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "使用谷歌学术检索助手搜索指定URL的结果 | 输入参数为谷歌学术搜索页的URL",
|
||||
"Function": HotReload(谷歌检索小助手)
|
||||
},
|
||||
"理解PDF文档内容 (模仿ChatPDF)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "理解PDF文档的内容并进行回答 | 输入参数为路径",
|
||||
"Function": HotReload(理解PDF文档内容标准文件输入)
|
||||
},
|
||||
"英文Latex项目全文润色(输入路径或上传压缩包)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "对英文Latex项目全文进行润色处理 | 输入参数为路径或上传压缩包",
|
||||
"Function": HotReload(Latex英文润色)
|
||||
},
|
||||
"英文Latex项目全文纠错(输入路径或上传压缩包)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "对英文Latex项目全文进行纠错处理 | 输入参数为路径或上传压缩包",
|
||||
"Function": HotReload(Latex英文纠错)
|
||||
},
|
||||
"中文Latex项目全文润色(输入路径或上传压缩包)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "对中文Latex项目全文进行润色处理 | 输入参数为路径或上传压缩包",
|
||||
"Function": HotReload(Latex中文润色)
|
||||
},
|
||||
"Latex项目全文中译英(输入路径或上传压缩包)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "对Latex项目全文进行中译英处理 | 输入参数为路径或上传压缩包",
|
||||
"Function": HotReload(Latex中译英)
|
||||
},
|
||||
"Latex项目全文英译中(输入路径或上传压缩包)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "对Latex项目全文进行英译中处理 | 输入参数为路径或上传压缩包",
|
||||
"Function": HotReload(Latex英译中)
|
||||
},
|
||||
"批量Markdown中译英(输入路径或上传压缩包)": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "批量将Markdown文件中文翻译为英文 | 输入参数为路径或上传压缩包",
|
||||
"Function": HotReload(Markdown中译英)
|
||||
},
|
||||
}
|
||||
@ -218,8 +272,10 @@ def get_crazy_functions():
|
||||
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)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
# "Info": "下载arxiv论文并翻译摘要 | 输入参数为arxiv编号如1812.10695",
|
||||
"Function": HotReload(下载arxiv论文并翻译摘要)
|
||||
}
|
||||
})
|
||||
@ -230,16 +286,20 @@ def get_crazy_functions():
|
||||
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(输入问题后点击该插件,需要访问谷歌)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
# "Info": "连接网络回答问题(需要访问谷歌)| 输入参数是一个问题",
|
||||
"Function": HotReload(连接网络回答问题)
|
||||
}
|
||||
})
|
||||
from crazy_functions.联网的ChatGPT_bing版 import 连接bing搜索回答问题
|
||||
function_plugins.update({
|
||||
"连接网络回答问题(中文Bing版,输入问题后点击该插件)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Info": "连接网络回答问题(需要访问中文Bing)| 输入参数是一个问题",
|
||||
"Function": HotReload(连接bing搜索回答问题)
|
||||
}
|
||||
})
|
||||
@ -250,6 +310,7 @@ def get_crazy_functions():
|
||||
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)": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True, # 调用时,唤起高级参数输入区(默认False)
|
||||
@ -264,6 +325,7 @@ def get_crazy_functions():
|
||||
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)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True, # 调用时,唤起高级参数输入区(默认False)
|
||||
@ -278,6 +340,7 @@ def get_crazy_functions():
|
||||
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)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True, # 调用时,唤起高级参数输入区(默认False)
|
||||
@ -293,6 +356,7 @@ def get_crazy_functions():
|
||||
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)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True,
|
||||
@ -308,8 +372,10 @@ def get_crazy_functions():
|
||||
from crazy_functions.数学动画生成manim import 动画生成
|
||||
function_plugins.update({
|
||||
"数学动画生成(Manim)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"Info": "按照自然语言描述生成一个动画 | 输入参数是一段话",
|
||||
"Function": HotReload(动画生成)
|
||||
}
|
||||
})
|
||||
@ -320,6 +386,7 @@ def get_crazy_functions():
|
||||
from crazy_functions.批量Markdown翻译 import Markdown翻译指定语言
|
||||
function_plugins.update({
|
||||
"Markdown翻译(手动指定语言)": {
|
||||
"Group": "编程",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True,
|
||||
@ -334,6 +401,7 @@ def get_crazy_functions():
|
||||
from crazy_functions.Langchain知识库 import 知识库问答
|
||||
function_plugins.update({
|
||||
"构建知识库(请先上传文件素材)": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True,
|
||||
@ -348,6 +416,7 @@ def get_crazy_functions():
|
||||
from crazy_functions.Langchain知识库 import 读取知识库作答
|
||||
function_plugins.update({
|
||||
"知识库问答": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True,
|
||||
@ -362,6 +431,7 @@ def get_crazy_functions():
|
||||
from crazy_functions.交互功能函数模板 import 交互功能模板函数
|
||||
function_plugins.update({
|
||||
"交互功能模板函数": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"Function": HotReload(交互功能模板函数)
|
||||
@ -374,6 +444,7 @@ def get_crazy_functions():
|
||||
from crazy_functions.Latex输出PDF结果 import Latex英文纠错加PDF对比
|
||||
function_plugins.update({
|
||||
"Latex英文纠错+高亮修正位置 [需Latex]": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True,
|
||||
@ -384,6 +455,7 @@ def get_crazy_functions():
|
||||
from crazy_functions.Latex输出PDF结果 import Latex翻译中文并重新编译PDF
|
||||
function_plugins.update({
|
||||
"Arixv论文精细翻译(输入arxivID)[需Latex]": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True,
|
||||
@ -391,11 +463,13 @@ def get_crazy_functions():
|
||||
"如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 " +
|
||||
"例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: " +
|
||||
'If the term "agent" is used in this section, it should be translated to "智能体". ',
|
||||
"Info": "Arixv论文精细翻译 | 输入参数arxiv论文的ID,比如1812.10695",
|
||||
"Function": HotReload(Latex翻译中文并重新编译PDF)
|
||||
}
|
||||
})
|
||||
function_plugins.update({
|
||||
"本地Latex论文精细翻译(上传Latex项目)[需Latex]": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"AdvancedArgs": True,
|
||||
@ -403,6 +477,7 @@ def get_crazy_functions():
|
||||
"如果有必要, 请在此处给出自定义翻译命令, 解决部分词汇翻译不准确的问题。 " +
|
||||
"例如当单词'agent'翻译不准确时, 请尝试把以下指令复制到高级参数区: " +
|
||||
'If the term "agent" is used in this section, it should be translated to "智能体". ',
|
||||
"Info": "本地Latex论文精细翻译 | 输入参数是路径",
|
||||
"Function": HotReload(Latex翻译中文并重新编译PDF)
|
||||
}
|
||||
})
|
||||
@ -416,8 +491,10 @@ def get_crazy_functions():
|
||||
from crazy_functions.语音助手 import 语音助手
|
||||
function_plugins.update({
|
||||
"实时音频采集": {
|
||||
"Group": "对话",
|
||||
"Color": "stop",
|
||||
"AsButton": True,
|
||||
"Info": "开始语言对话 | 没有输入参数",
|
||||
"Function": HotReload(语音助手)
|
||||
}
|
||||
})
|
||||
@ -425,17 +502,32 @@ def get_crazy_functions():
|
||||
print('Load function plugin failed')
|
||||
|
||||
try:
|
||||
from crazy_functions.虚空终端 import 自动终端
|
||||
from crazy_functions.批量翻译PDF文档_NOUGAT import 批量翻译PDF文档
|
||||
function_plugins.update({
|
||||
"自动终端": {
|
||||
"精准翻译PDF文档(NOUGAT)": {
|
||||
"Group": "学术",
|
||||
"Color": "stop",
|
||||
"AsButton": False,
|
||||
"Function": HotReload(自动终端)
|
||||
"Function": HotReload(批量翻译PDF文档)
|
||||
}
|
||||
})
|
||||
except:
|
||||
print('Load function plugin failed')
|
||||
|
||||
|
||||
# try:
|
||||
# from crazy_functions.CodeInterpreter import 虚空终端CodeInterpreter
|
||||
# function_plugins.update({
|
||||
# "CodeInterpreter(开发中,仅供测试)": {
|
||||
# "Group": "编程|对话",
|
||||
# "Color": "stop",
|
||||
# "AsButton": False,
|
||||
# "Function": HotReload(虚空终端CodeInterpreter)
|
||||
# }
|
||||
# })
|
||||
# except:
|
||||
# print('Load function plugin failed')
|
||||
|
||||
# try:
|
||||
# from crazy_functions.chatglm微调工具 import 微调数据集生成
|
||||
# function_plugins.update({
|
||||
@ -449,4 +541,24 @@ def get_crazy_functions():
|
||||
# })
|
||||
# except:
|
||||
# print('Load function plugin failed')
|
||||
|
||||
|
||||
|
||||
"""
|
||||
设置默认值:
|
||||
- 默认 Group = 对话
|
||||
- 默认 AsButton = True
|
||||
- 默认 AdvancedArgs = False
|
||||
- 默认 Color = secondary
|
||||
"""
|
||||
for name, function_meta in function_plugins.items():
|
||||
if "Group" not in function_meta:
|
||||
function_plugins[name]["Group"] = '对话'
|
||||
if "AsButton" not in function_meta:
|
||||
function_plugins[name]["AsButton"] = True
|
||||
if "AdvancedArgs" not in function_meta:
|
||||
function_plugins[name]["AdvancedArgs"] = False
|
||||
if "Color" not in function_meta:
|
||||
function_plugins[name]["Color"] = 'secondary'
|
||||
|
||||
return function_plugins
|
||||
|
231
crazy_functions/CodeInterpreter.py
Normal file
231
crazy_functions/CodeInterpreter.py
Normal file
@ -0,0 +1,231 @@
|
||||
from collections.abc import Callable, Iterable, Mapping
|
||||
from typing import Any
|
||||
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, promote_file_to_downloadzone, clear_file_downloadzone
|
||||
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||
from .crazy_utils import input_clipping, try_install_deps
|
||||
from multiprocessing import Process, Pipe
|
||||
import os
|
||||
import time
|
||||
|
||||
templete = """
|
||||
```python
|
||||
import ... # Put dependencies here, e.g. import numpy as np
|
||||
|
||||
class TerminalFunction(object): # Do not change the name of the class, The name of the class must be `TerminalFunction`
|
||||
|
||||
def run(self, path): # The name of the function must be `run`, it takes only a positional argument.
|
||||
# rewrite the function you have just written here
|
||||
...
|
||||
return generated_file_path
|
||||
```
|
||||
"""
|
||||
|
||||
def inspect_dependency(chatbot, history):
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return True
|
||||
|
||||
def get_code_block(reply):
|
||||
import re
|
||||
pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks
|
||||
matches = re.findall(pattern, reply) # find all code blocks in text
|
||||
if len(matches) == 1:
|
||||
return matches[0].strip('python') # code block
|
||||
for match in matches:
|
||||
if 'class TerminalFunction' in match:
|
||||
return match.strip('python') # code block
|
||||
raise RuntimeError("GPT is not generating proper code.")
|
||||
|
||||
def gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history):
|
||||
# 输入
|
||||
prompt_compose = [
|
||||
f'Your job:\n'
|
||||
f'1. write a single Python function, which takes a path of a `{file_type}` file as the only argument and returns a `string` containing the result of analysis or the path of generated files. \n',
|
||||
f"2. You should write this function to perform following task: " + txt + "\n",
|
||||
f"3. Wrap the output python function with markdown codeblock."
|
||||
]
|
||||
i_say = "".join(prompt_compose)
|
||||
demo = []
|
||||
|
||||
# 第一步
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=i_say,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=demo,
|
||||
sys_prompt= r"You are a programmer."
|
||||
)
|
||||
history.extend([i_say, gpt_say])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
|
||||
# 第二步
|
||||
prompt_compose = [
|
||||
"If previous stage is successful, rewrite the function you have just written to satisfy following templete: \n",
|
||||
templete
|
||||
]
|
||||
i_say = "".join(prompt_compose); inputs_show_user = "If previous stage is successful, rewrite the function you have just written to satisfy executable templete. "
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=i_say, inputs_show_user=inputs_show_user,
|
||||
llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
|
||||
sys_prompt= r"You are a programmer."
|
||||
)
|
||||
code_to_return = gpt_say
|
||||
history.extend([i_say, gpt_say])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
|
||||
# # 第三步
|
||||
# i_say = "Please list to packages to install to run the code above. Then show me how to use `try_install_deps` function to install them."
|
||||
# i_say += 'For instance. `try_install_deps(["opencv-python", "scipy", "numpy"])`'
|
||||
# installation_advance = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
# inputs=i_say, inputs_show_user=inputs_show_user,
|
||||
# llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
|
||||
# sys_prompt= r"You are a programmer."
|
||||
# )
|
||||
# # # 第三步
|
||||
# i_say = "Show me how to use `pip` to install packages to run the code above. "
|
||||
# i_say += 'For instance. `pip install -r opencv-python scipy numpy`'
|
||||
# installation_advance = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
# inputs=i_say, inputs_show_user=i_say,
|
||||
# llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
|
||||
# sys_prompt= r"You are a programmer."
|
||||
# )
|
||||
installation_advance = ""
|
||||
|
||||
return code_to_return, installation_advance, txt, file_type, llm_kwargs, chatbot, history
|
||||
|
||||
def make_module(code):
|
||||
module_file = 'gpt_fn_' + gen_time_str().replace('-','_')
|
||||
with open(f'gpt_log/{module_file}.py', 'w', encoding='utf8') as f:
|
||||
f.write(code)
|
||||
|
||||
def get_class_name(class_string):
|
||||
import re
|
||||
# Use regex to extract the class name
|
||||
class_name = re.search(r'class (\w+)\(', class_string).group(1)
|
||||
return class_name
|
||||
|
||||
class_name = get_class_name(code)
|
||||
return f"gpt_log.{module_file}->{class_name}"
|
||||
|
||||
def init_module_instance(module):
|
||||
import importlib
|
||||
module_, class_ = module.split('->')
|
||||
init_f = getattr(importlib.import_module(module_), class_)
|
||||
return init_f()
|
||||
|
||||
def for_immediate_show_off_when_possible(file_type, fp, chatbot):
|
||||
if file_type in ['png', 'jpg']:
|
||||
image_path = os.path.abspath(fp)
|
||||
chatbot.append(['这是一张图片, 展示如下:',
|
||||
f'本地文件地址: <br/>`{image_path}`<br/>'+
|
||||
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
|
||||
])
|
||||
return chatbot
|
||||
|
||||
def subprocess_worker(instance, file_path, return_dict):
|
||||
return_dict['result'] = instance.run(file_path)
|
||||
|
||||
def have_any_recent_upload_files(chatbot):
|
||||
_5min = 5 * 60
|
||||
if not chatbot: return False # chatbot is None
|
||||
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
|
||||
if not most_recent_uploaded: return False # most_recent_uploaded is None
|
||||
if time.time() - most_recent_uploaded["time"] < _5min: return True # most_recent_uploaded is new
|
||||
else: return False # most_recent_uploaded is too old
|
||||
|
||||
def get_recent_file_prompt_support(chatbot):
|
||||
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
|
||||
path = most_recent_uploaded['path']
|
||||
return path
|
||||
|
||||
@CatchException
|
||||
def 虚空终端CodeInterpreter(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
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
# 清空历史,以免输入溢出
|
||||
history = []; clear_file_downloadzone(chatbot)
|
||||
|
||||
# 基本信息:功能、贡献者
|
||||
chatbot.append([
|
||||
"函数插件功能?",
|
||||
"CodeInterpreter开源版, 此插件处于开发阶段, 建议暂时不要使用, 插件初始化中 ..."
|
||||
])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
if have_any_recent_upload_files(chatbot):
|
||||
file_path = get_recent_file_prompt_support(chatbot)
|
||||
else:
|
||||
chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
# 读取文件
|
||||
if ("recently_uploaded_files" in plugin_kwargs) and (plugin_kwargs["recently_uploaded_files"] == ""): plugin_kwargs.pop("recently_uploaded_files")
|
||||
recently_uploaded_files = plugin_kwargs.get("recently_uploaded_files", None)
|
||||
file_path = recently_uploaded_files[-1]
|
||||
file_type = file_path.split('.')[-1]
|
||||
|
||||
# 粗心检查
|
||||
if 'private_upload' in txt:
|
||||
chatbot.append([
|
||||
"...",
|
||||
f"请在输入框内填写需求,然后再次点击该插件(文件路径 {file_path} 已经被记忆)"
|
||||
])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
# 开始干正事
|
||||
for j in range(5): # 最多重试5次
|
||||
try:
|
||||
code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \
|
||||
yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history)
|
||||
code = get_code_block(code)
|
||||
res = make_module(code)
|
||||
instance = init_module_instance(res)
|
||||
break
|
||||
except Exception as e:
|
||||
chatbot.append([f"第{j}次代码生成尝试,失败了", f"错误追踪\n```\n{trimmed_format_exc()}\n```\n"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
# 代码生成结束, 开始执行
|
||||
try:
|
||||
import multiprocessing
|
||||
manager = multiprocessing.Manager()
|
||||
return_dict = manager.dict()
|
||||
|
||||
p = multiprocessing.Process(target=subprocess_worker, args=(instance, file_path, return_dict))
|
||||
# only has 10 seconds to run
|
||||
p.start(); p.join(timeout=10)
|
||||
if p.is_alive(): p.terminate(); p.join()
|
||||
p.close()
|
||||
res = return_dict['result']
|
||||
# res = instance.run(file_path)
|
||||
except Exception as e:
|
||||
chatbot.append(["执行失败了", f"错误追踪\n```\n{trimmed_format_exc()}\n```\n"])
|
||||
# chatbot.append(["如果是缺乏依赖,请参考以下建议", installation_advance])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
# 顺利完成,收尾
|
||||
res = str(res)
|
||||
if os.path.exists(res):
|
||||
chatbot.append(["执行成功了,结果是一个有效文件", "结果:" + res])
|
||||
new_file_path = promote_file_to_downloadzone(res, chatbot=chatbot)
|
||||
chatbot = for_immediate_show_off_when_possible(file_type, new_file_path, chatbot)
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
else:
|
||||
chatbot.append(["执行成功了,结果是一个字符串", "结果:" + res])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
|
||||
|
||||
"""
|
||||
测试:
|
||||
裁剪图像,保留下半部分
|
||||
交换图像的蓝色通道和红色通道
|
||||
将图像转为灰度图像
|
||||
将csv文件转excel表格
|
||||
"""
|
@ -6,7 +6,7 @@ pj = os.path.join
|
||||
ARXIV_CACHE_DIR = os.path.expanduser(f"~/arxiv_cache/")
|
||||
|
||||
# =================================== 工具函数 ===============================================
|
||||
专业词汇声明 = 'If the term "agent" is used in this section, it should be translated to "智能体". '
|
||||
# 专业词汇声明 = 'If the term "agent" is used in this section, it should be translated to "智能体". '
|
||||
def switch_prompt(pfg, mode, more_requirement):
|
||||
"""
|
||||
Generate prompts and system prompts based on the mode for proofreading or translating.
|
||||
@ -109,7 +109,7 @@ def arxiv_download(chatbot, history, txt):
|
||||
|
||||
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_}"
|
||||
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 ------------->
|
||||
@ -255,7 +255,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
|
||||
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}")
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无法处理: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
@ -291,7 +291,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
|
||||
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||
promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
|
||||
else:
|
||||
chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果(压缩包), 内含已经翻译的Tex文档, 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 ...'))
|
||||
chatbot.append((f"失败了", '虽然PDF生成失败了, 但请查收结果(压缩包), 内含已经翻译的Tex文档, 您可以到Github Issue区, 用该压缩包进行反馈。如系统是Linux,请检查系统字体(见Github wiki) ...'))
|
||||
yield from update_ui(chatbot=chatbot, history=history); time.sleep(1) # 刷新界面
|
||||
promote_file_to_downloadzone(file=zip_res, chatbot=chatbot)
|
||||
|
||||
|
@ -591,11 +591,16 @@ def get_files_from_everything(txt, type): # type='.md'
|
||||
# 网络的远程文件
|
||||
import requests
|
||||
from toolbox import get_conf
|
||||
from toolbox import get_log_folder, gen_time_str
|
||||
proxies, = get_conf('proxies')
|
||||
r = requests.get(txt, proxies=proxies)
|
||||
with open('./gpt_log/temp'+type, 'wb+') as f: f.write(r.content)
|
||||
project_folder = './gpt_log/'
|
||||
file_manifest = ['./gpt_log/temp'+type]
|
||||
try:
|
||||
r = requests.get(txt, proxies=proxies)
|
||||
except:
|
||||
raise ConnectionRefusedError(f"无法下载资源{txt},请检查。")
|
||||
path = os.path.join(get_log_folder(plugin_name='web_download'), gen_time_str()+type)
|
||||
with open(path, 'wb+') as f: f.write(r.content)
|
||||
project_folder = get_log_folder(plugin_name='web_download')
|
||||
file_manifest = [path]
|
||||
elif txt.endswith(type):
|
||||
# 直接给定文件
|
||||
file_manifest = [txt]
|
||||
|
@ -37,10 +37,19 @@ Here is the output schema:
|
||||
{schema}
|
||||
```"""
|
||||
|
||||
|
||||
PYDANTIC_FORMAT_INSTRUCTIONS_SIMPLE = """The output should be formatted as a JSON instance that conforms to the JSON schema below.
|
||||
```
|
||||
{schema}
|
||||
```"""
|
||||
|
||||
class JsonStringError(Exception): ...
|
||||
|
||||
class GptJsonIO():
|
||||
|
||||
def __init__(self, schema):
|
||||
def __init__(self, schema, example_instruction=True):
|
||||
self.pydantic_object = schema
|
||||
self.example_instruction = example_instruction
|
||||
self.format_instructions = self.generate_format_instructions()
|
||||
|
||||
def generate_format_instructions(self):
|
||||
@ -53,9 +62,11 @@ class GptJsonIO():
|
||||
if "type" in reduced_schema:
|
||||
del reduced_schema["type"]
|
||||
# Ensure json in context is well-formed with double quotes.
|
||||
schema_str = json.dumps(reduced_schema)
|
||||
|
||||
return PYDANTIC_FORMAT_INSTRUCTIONS.format(schema=schema_str)
|
||||
if self.example_instruction:
|
||||
schema_str = json.dumps(reduced_schema)
|
||||
return PYDANTIC_FORMAT_INSTRUCTIONS.format(schema=schema_str)
|
||||
else:
|
||||
return PYDANTIC_FORMAT_INSTRUCTIONS_SIMPLE.format(schema=schema_str)
|
||||
|
||||
def generate_output(self, text):
|
||||
# Greedy search for 1st json candidate.
|
||||
@ -95,6 +106,6 @@ class GptJsonIO():
|
||||
except Exception as e:
|
||||
# 没辙了,放弃治疗
|
||||
logging.info('Repaire json fail.')
|
||||
raise RuntimeError('Cannot repair json.', str(e))
|
||||
raise JsonStringError('Cannot repair json.', str(e))
|
||||
return result
|
||||
|
||||
|
@ -1,4 +1,4 @@
|
||||
import time, threading, json
|
||||
import time, logging, json
|
||||
|
||||
|
||||
class AliyunASR():
|
||||
@ -12,14 +12,14 @@ class AliyunASR():
|
||||
message = json.loads(message)
|
||||
self.parsed_sentence = message['payload']['result']
|
||||
self.event_on_entence_end.set()
|
||||
print(self.parsed_sentence)
|
||||
# print(self.parsed_sentence)
|
||||
|
||||
def test_on_start(self, message, *args):
|
||||
# print("test_on_start:{}".format(message))
|
||||
pass
|
||||
|
||||
def test_on_error(self, message, *args):
|
||||
print("on_error args=>{}".format(args))
|
||||
logging.error("on_error args=>{}".format(args))
|
||||
pass
|
||||
|
||||
def test_on_close(self, *args):
|
||||
@ -36,7 +36,6 @@ class AliyunASR():
|
||||
# print("on_completed:args=>{} message=>{}".format(args, message))
|
||||
pass
|
||||
|
||||
|
||||
def audio_convertion_thread(self, uuid):
|
||||
# 在一个异步线程中采集音频
|
||||
import nls # pip install git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
|
||||
|
@ -20,6 +20,11 @@ def get_avail_grobid_url():
|
||||
def parse_pdf(pdf_path, grobid_url):
|
||||
import scipdf # pip install scipdf_parser
|
||||
if grobid_url.endswith('/'): grobid_url = grobid_url.rstrip('/')
|
||||
article_dict = scipdf.parse_pdf_to_dict(pdf_path, grobid_url=grobid_url)
|
||||
try:
|
||||
article_dict = scipdf.parse_pdf_to_dict(pdf_path, grobid_url=grobid_url)
|
||||
except GROBID_OFFLINE_EXCEPTION:
|
||||
raise GROBID_OFFLINE_EXCEPTION("GROBID服务不可用,请修改config中的GROBID_URL,可修改成本地GROBID服务。")
|
||||
except:
|
||||
raise RuntimeError("解析PDF失败,请检查PDF是否损坏。")
|
||||
return article_dict
|
||||
|
||||
|
@ -1,9 +1,9 @@
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import List
|
||||
from toolbox import update_ui_lastest_msg, get_conf
|
||||
from toolbox import update_ui_lastest_msg, disable_auto_promotion
|
||||
from request_llm.bridge_all import predict_no_ui_long_connection
|
||||
from crazy_functions.json_fns.pydantic_io import GptJsonIO
|
||||
import copy, json, pickle, os, sys
|
||||
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
|
||||
import copy, json, pickle, os, sys, time
|
||||
|
||||
|
||||
def read_avail_plugin_enum():
|
||||
@ -11,37 +11,85 @@ def read_avail_plugin_enum():
|
||||
plugin_arr = get_crazy_functions()
|
||||
# remove plugins with out explaination
|
||||
plugin_arr = {k:v for k, v in plugin_arr.items() if 'Info' in v}
|
||||
plugin_arr_info = {"F{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)}
|
||||
plugin_arr_dict = {"F{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
|
||||
plugin_arr_info = {"F_{:04d}".format(i):v["Info"] for i, v in enumerate(plugin_arr.values(), start=1)}
|
||||
plugin_arr_dict = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
|
||||
plugin_arr_dict_parse = {"F_{:04d}".format(i):v for i, v in enumerate(plugin_arr.values(), start=1)}
|
||||
plugin_arr_dict_parse.update({f"F_{i}":v for i, v in enumerate(plugin_arr.values(), start=1)})
|
||||
prompt = json.dumps(plugin_arr_info, ensure_ascii=False, indent=2)
|
||||
prompt = "\n\nThe defination of PluginEnum:\nPluginEnum=" + prompt
|
||||
return prompt, plugin_arr_dict
|
||||
return prompt, plugin_arr_dict, plugin_arr_dict_parse
|
||||
|
||||
def wrap_code(txt):
|
||||
txt = txt.replace('```','')
|
||||
return f"\n```\n{txt}\n```\n"
|
||||
|
||||
def have_any_recent_upload_files(chatbot):
|
||||
_5min = 5 * 60
|
||||
if not chatbot: return False # chatbot is None
|
||||
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
|
||||
if not most_recent_uploaded: return False # most_recent_uploaded is None
|
||||
if time.time() - most_recent_uploaded["time"] < _5min: return True # most_recent_uploaded is new
|
||||
else: return False # most_recent_uploaded is too old
|
||||
|
||||
def get_recent_file_prompt_support(chatbot):
|
||||
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
|
||||
path = most_recent_uploaded['path']
|
||||
prompt = "\nAdditional Information:\n"
|
||||
prompt = "In case that this plugin requires a path or a file as argument,"
|
||||
prompt += f"it is important for you to know that the user has recently uploaded a file, located at: `{path}`"
|
||||
prompt += f"Only use it when necessary, otherwise, you can ignore this file."
|
||||
return prompt
|
||||
|
||||
def get_inputs_show_user(inputs, plugin_arr_enum_prompt):
|
||||
# remove plugin_arr_enum_prompt from inputs string
|
||||
inputs_show_user = inputs.replace(plugin_arr_enum_prompt, "")
|
||||
inputs_show_user += plugin_arr_enum_prompt[:200] + '...'
|
||||
inputs_show_user += '\n...\n'
|
||||
inputs_show_user += '...\n'
|
||||
inputs_show_user += '...}'
|
||||
return inputs_show_user
|
||||
|
||||
def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
|
||||
plugin_arr_enum_prompt, plugin_arr_dict = read_avail_plugin_enum()
|
||||
plugin_arr_enum_prompt, plugin_arr_dict, plugin_arr_dict_parse = read_avail_plugin_enum()
|
||||
class Plugin(BaseModel):
|
||||
plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F0000000000000")
|
||||
plugin_arg: str = Field(description="The argument of the plugin. A path or url or empty.", default="")
|
||||
|
||||
plugin_selection: str = Field(description="The most related plugin from one of the PluginEnum.", default="F_0000")
|
||||
reason_of_selection: str = Field(description="The reason why you should select this plugin.", default="This plugin satisfy user requirement most")
|
||||
# ⭐ ⭐ ⭐ 选择插件
|
||||
yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n查找可用插件中...", chatbot=chatbot, history=history, delay=0)
|
||||
gpt_json_io = GptJsonIO(Plugin)
|
||||
gpt_json_io.format_instructions = "The format of your output should be a json that can be parsed by json.loads.\n"
|
||||
gpt_json_io.format_instructions += """Output example: {"plugin_selection":"F_1234", "reason_of_selection":"F_1234 plugin satisfy user requirement most"}\n"""
|
||||
gpt_json_io.format_instructions += "The plugins you are authorized to use are listed below:\n"
|
||||
gpt_json_io.format_instructions += plugin_arr_enum_prompt
|
||||
inputs = "Choose the correct plugin and extract plugin_arg, the user requirement is: \n\n" + \
|
||||
">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
|
||||
gpt_json_io.format_instructions
|
||||
inputs = "Choose the correct plugin according to user requirements, the user requirement is: \n\n" + \
|
||||
">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + gpt_json_io.format_instructions
|
||||
|
||||
run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(
|
||||
inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
|
||||
plugin_sel = gpt_json_io.generate_output_auto_repair(run_gpt_fn(inputs, ""), run_gpt_fn)
|
||||
|
||||
if plugin_sel.plugin_selection not in plugin_arr_dict:
|
||||
msg = f'找不到合适插件执行该任务'
|
||||
try:
|
||||
gpt_reply = run_gpt_fn(inputs, "")
|
||||
plugin_sel = gpt_json_io.generate_output_auto_repair(gpt_reply, run_gpt_fn)
|
||||
except JsonStringError:
|
||||
msg = f"抱歉, {llm_kwargs['llm_model']}无法理解您的需求。"
|
||||
msg += "请求的Prompt为:\n" + wrap_code(get_inputs_show_user(inputs, plugin_arr_enum_prompt))
|
||||
msg += "语言模型回复为:\n" + wrap_code(gpt_reply)
|
||||
msg += "\n但您可以尝试再试一次\n"
|
||||
yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
||||
return
|
||||
if plugin_sel.plugin_selection not in plugin_arr_dict_parse:
|
||||
msg = f"抱歉, 找不到合适插件执行该任务, 或者{llm_kwargs['llm_model']}无法理解您的需求。"
|
||||
msg += f"语言模型{llm_kwargs['llm_model']}选择了不存在的插件:\n" + wrap_code(gpt_reply)
|
||||
msg += "\n但您可以尝试再试一次\n"
|
||||
yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
||||
return
|
||||
|
||||
# ⭐ ⭐ ⭐ 确认插件参数
|
||||
plugin = plugin_arr_dict[plugin_sel.plugin_selection]
|
||||
if not have_any_recent_upload_files(chatbot):
|
||||
appendix_info = ""
|
||||
else:
|
||||
appendix_info = get_recent_file_prompt_support(chatbot)
|
||||
|
||||
plugin = plugin_arr_dict_parse[plugin_sel.plugin_selection]
|
||||
yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n提取插件参数...", chatbot=chatbot, history=history, delay=0)
|
||||
class PluginExplicit(BaseModel):
|
||||
plugin_selection: str = plugin_sel.plugin_selection
|
||||
@ -50,7 +98,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
|
||||
gpt_json_io.format_instructions += "The information about this plugin is:" + plugin["Info"]
|
||||
inputs = f"A plugin named {plugin_sel.plugin_selection} is selected, " + \
|
||||
"you should extract plugin_arg from the user requirement, the user requirement is: \n\n" + \
|
||||
">> " + txt.rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
|
||||
">> " + (txt + appendix_info).rstrip('\n').replace('\n','\n>> ') + '\n\n' + \
|
||||
gpt_json_io.format_instructions
|
||||
run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(
|
||||
inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
|
||||
@ -60,7 +108,7 @@ def execute_plugin(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prom
|
||||
# ⭐ ⭐ ⭐ 执行插件
|
||||
fn = plugin['Function']
|
||||
fn_name = fn.__name__
|
||||
msg = f'正在调用插件: {fn_name}\n\n插件说明:{plugin["Info"]}\n\n插件参数:{plugin_sel.plugin_arg}'
|
||||
msg = f'{llm_kwargs["llm_model"]}为您选择了插件: `{fn_name}`\n\n插件说明:{plugin["Info"]}\n\n插件参数:{plugin_sel.plugin_arg}\n\n假如偏离了您的要求,按停止键终止。'
|
||||
yield from update_ui_lastest_msg(lastmsg=msg, chatbot=chatbot, history=history, delay=2)
|
||||
yield from fn(plugin_sel.plugin_arg, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, -1)
|
||||
return
|
28
crazy_functions/vt_fns/vt_state.py
Normal file
28
crazy_functions/vt_fns/vt_state.py
Normal file
@ -0,0 +1,28 @@
|
||||
import pickle
|
||||
|
||||
class VoidTerminalState():
|
||||
def __init__(self):
|
||||
self.reset_state()
|
||||
|
||||
def reset_state(self):
|
||||
self.has_provided_explaination = False
|
||||
|
||||
def lock_plugin(self, chatbot):
|
||||
chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端'
|
||||
chatbot._cookies['plugin_state'] = pickle.dumps(self)
|
||||
|
||||
def unlock_plugin(self, chatbot):
|
||||
self.reset_state()
|
||||
chatbot._cookies['lock_plugin'] = None
|
||||
chatbot._cookies['plugin_state'] = pickle.dumps(self)
|
||||
|
||||
def set_state(self, chatbot, key, value):
|
||||
setattr(self, key, value)
|
||||
chatbot._cookies['plugin_state'] = pickle.dumps(self)
|
||||
|
||||
def get_state(chatbot):
|
||||
state = chatbot._cookies.get('plugin_state', None)
|
||||
if state is not None: state = pickle.loads(state)
|
||||
else: state = VoidTerminalState()
|
||||
state.chatbot = chatbot
|
||||
return state
|
271
crazy_functions/批量翻译PDF文档_NOUGAT.py
Normal file
271
crazy_functions/批量翻译PDF文档_NOUGAT.py
Normal file
@ -0,0 +1,271 @@
|
||||
from toolbox import CatchException, report_execption, gen_time_str
|
||||
from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
|
||||
from toolbox import write_history_to_file, get_log_folder
|
||||
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
|
||||
from .crazy_utils import read_and_clean_pdf_text
|
||||
from .pdf_fns.parse_pdf import parse_pdf, get_avail_grobid_url
|
||||
from colorful import *
|
||||
import os
|
||||
import math
|
||||
import logging
|
||||
|
||||
def markdown_to_dict(article_content):
|
||||
import markdown
|
||||
from bs4 import BeautifulSoup
|
||||
cur_t = ""
|
||||
cur_c = ""
|
||||
results = {}
|
||||
for line in article_content:
|
||||
if line.startswith('#'):
|
||||
if cur_t!="":
|
||||
if cur_t not in results:
|
||||
results.update({cur_t:cur_c.lstrip('\n')})
|
||||
else:
|
||||
# 处理重名的章节
|
||||
results.update({cur_t + " " + gen_time_str():cur_c.lstrip('\n')})
|
||||
cur_t = line.rstrip('\n')
|
||||
cur_c = ""
|
||||
else:
|
||||
cur_c += line
|
||||
results_final = {}
|
||||
for k in list(results.keys()):
|
||||
if k.startswith('# '):
|
||||
results_final['title'] = k.split('# ')[-1]
|
||||
results_final['authors'] = results.pop(k).lstrip('\n')
|
||||
if k.startswith('###### Abstract'):
|
||||
results_final['abstract'] = results.pop(k).lstrip('\n')
|
||||
|
||||
results_final_sections = []
|
||||
for k,v in results.items():
|
||||
results_final_sections.append({
|
||||
'heading':k.lstrip("# "),
|
||||
'text':v if len(v) > 0 else f"The beginning of {k.lstrip('# ')} section."
|
||||
})
|
||||
results_final['sections'] = results_final_sections
|
||||
return results_final
|
||||
|
||||
|
||||
@CatchException
|
||||
def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
|
||||
disable_auto_promotion(chatbot)
|
||||
# 基本信息:功能、贡献者
|
||||
chatbot.append([
|
||||
"函数插件功能?",
|
||||
"批量翻译PDF文档。函数插件贡献者: Binary-Husky"])
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
# 尝试导入依赖,如果缺少依赖,则给出安装建议
|
||||
try:
|
||||
import nougat
|
||||
import tiktoken
|
||||
except:
|
||||
report_execption(chatbot, history,
|
||||
a=f"解析项目: {txt}",
|
||||
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade nougat-ocr tiktoken```。")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
# 清空历史,以免输入溢出
|
||||
history = []
|
||||
|
||||
from .crazy_utils import get_files_from_everything
|
||||
success, file_manifest, project_folder = get_files_from_everything(txt, type='.pdf')
|
||||
# 检测输入参数,如没有给定输入参数,直接退出
|
||||
if not success:
|
||||
if txt == "": txt = '空空如也的输入栏'
|
||||
|
||||
# 如果没找到任何文件
|
||||
if len(file_manifest) == 0:
|
||||
report_execption(chatbot, history,
|
||||
a=f"解析项目: {txt}", b=f"找不到任何.tex或.pdf文件: {txt}")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
# 开始正式执行任务
|
||||
yield from 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
|
||||
|
||||
|
||||
def nougat_with_timeout(command, cwd, timeout=3600):
|
||||
import subprocess
|
||||
process = subprocess.Popen(command, shell=True, cwd=cwd)
|
||||
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 NOUGAT_parse_pdf(fp):
|
||||
import glob
|
||||
from toolbox import get_log_folder, gen_time_str
|
||||
dst = os.path.join(get_log_folder(plugin_name='nougat'), gen_time_str())
|
||||
os.makedirs(dst)
|
||||
nougat_with_timeout(f'nougat --out "{os.path.abspath(dst)}" "{os.path.abspath(fp)}"', os.getcwd())
|
||||
res = glob.glob(os.path.join(dst,'*.mmd'))
|
||||
if len(res) == 0:
|
||||
raise RuntimeError("Nougat解析论文失败。")
|
||||
return res[0]
|
||||
|
||||
|
||||
def 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
|
||||
import copy
|
||||
import tiktoken
|
||||
TOKEN_LIMIT_PER_FRAGMENT = 1280
|
||||
generated_conclusion_files = []
|
||||
generated_html_files = []
|
||||
DST_LANG = "中文"
|
||||
for index, fp in enumerate(file_manifest):
|
||||
chatbot.append(["当前进度:", f"正在解析论文,请稍候。(第一次运行时,需要花费较长时间下载NOUGAT参数)"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
fpp = NOUGAT_parse_pdf(fp)
|
||||
|
||||
with open(fpp, 'r', encoding='utf8') as f:
|
||||
article_content = f.readlines()
|
||||
article_dict = markdown_to_dict(article_content)
|
||||
logging.info(article_dict)
|
||||
|
||||
prompt = "以下是一篇学术论文的基本信息:\n"
|
||||
# title
|
||||
title = article_dict.get('title', '无法获取 title'); prompt += f'title:{title}\n\n'
|
||||
# authors
|
||||
authors = article_dict.get('authors', '无法获取 authors'); prompt += f'authors:{authors}\n\n'
|
||||
# abstract
|
||||
abstract = article_dict.get('abstract', '无法获取 abstract'); prompt += f'abstract:{abstract}\n\n'
|
||||
# command
|
||||
prompt += f"请将题目和摘要翻译为{DST_LANG}。"
|
||||
meta = [f'# Title:\n\n', title, f'# Abstract:\n\n', abstract ]
|
||||
|
||||
# 单线,获取文章meta信息
|
||||
paper_meta_info = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=prompt,
|
||||
inputs_show_user=prompt,
|
||||
llm_kwargs=llm_kwargs,
|
||||
chatbot=chatbot, history=[],
|
||||
sys_prompt="You are an academic paper reader。",
|
||||
)
|
||||
|
||||
# 多线,翻译
|
||||
inputs_array = []
|
||||
inputs_show_user_array = []
|
||||
|
||||
# get_token_num
|
||||
from request_llm.bridge_all import model_info
|
||||
enc = model_info[llm_kwargs['llm_model']]['tokenizer']
|
||||
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
|
||||
from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
|
||||
|
||||
def break_down(txt):
|
||||
raw_token_num = get_token_num(txt)
|
||||
if raw_token_num <= TOKEN_LIMIT_PER_FRAGMENT:
|
||||
return [txt]
|
||||
else:
|
||||
# raw_token_num > TOKEN_LIMIT_PER_FRAGMENT
|
||||
# find a smooth token limit to achieve even seperation
|
||||
count = int(math.ceil(raw_token_num / TOKEN_LIMIT_PER_FRAGMENT))
|
||||
token_limit_smooth = raw_token_num // count + count
|
||||
return breakdown_txt_to_satisfy_token_limit_for_pdf(txt, get_token_fn=get_token_num, limit=token_limit_smooth)
|
||||
|
||||
for section in article_dict.get('sections'):
|
||||
if len(section['text']) == 0: continue
|
||||
section_frags = break_down(section['text'])
|
||||
for i, fragment in enumerate(section_frags):
|
||||
heading = section['heading']
|
||||
if len(section_frags) > 1: heading += f' Part-{i+1}'
|
||||
inputs_array.append(
|
||||
f"你需要翻译{heading}章节,内容如下: \n\n{fragment}"
|
||||
)
|
||||
inputs_show_user_array.append(
|
||||
f"# {heading}\n\n{fragment}"
|
||||
)
|
||||
|
||||
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=[meta for _ in inputs_array],
|
||||
sys_prompt_array=[
|
||||
"请你作为一个学术翻译,负责把学术论文准确翻译成中文。注意文章中的每一句话都要翻译。" for _ in inputs_array],
|
||||
)
|
||||
res_path = write_history_to_file(meta + ["# Meta Translation" , paper_meta_info] + gpt_response_collection, file_basename=None, file_fullname=None)
|
||||
promote_file_to_downloadzone(res_path, rename_file=os.path.basename(fp)+'.md', chatbot=chatbot)
|
||||
generated_conclusion_files.append(res_path)
|
||||
|
||||
ch = construct_html()
|
||||
orig = ""
|
||||
trans = ""
|
||||
gpt_response_collection_html = copy.deepcopy(gpt_response_collection)
|
||||
for i,k in enumerate(gpt_response_collection_html):
|
||||
if i%2==0:
|
||||
gpt_response_collection_html[i] = inputs_show_user_array[i//2]
|
||||
else:
|
||||
gpt_response_collection_html[i] = gpt_response_collection_html[i]
|
||||
|
||||
final = ["", "", "一、论文概况", "", "Abstract", paper_meta_info, "二、论文翻译", ""]
|
||||
final.extend(gpt_response_collection_html)
|
||||
for i, k in enumerate(final):
|
||||
if i%2==0:
|
||||
orig = k
|
||||
if i%2==1:
|
||||
trans = k
|
||||
ch.add_row(a=orig, b=trans)
|
||||
create_report_file_name = f"{os.path.basename(fp)}.trans.html"
|
||||
html_file = ch.save_file(create_report_file_name)
|
||||
generated_html_files.append(html_file)
|
||||
promote_file_to_downloadzone(html_file, rename_file=os.path.basename(html_file), chatbot=chatbot)
|
||||
|
||||
chatbot.append(("给出输出文件清单", str(generated_conclusion_files + generated_html_files)))
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
|
||||
|
||||
class construct_html():
|
||||
def __init__(self) -> None:
|
||||
self.css = """
|
||||
.row {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
}
|
||||
|
||||
.column {
|
||||
flex: 1;
|
||||
padding: 10px;
|
||||
}
|
||||
|
||||
.table-header {
|
||||
font-weight: bold;
|
||||
border-bottom: 1px solid black;
|
||||
}
|
||||
|
||||
.table-row {
|
||||
border-bottom: 1px solid lightgray;
|
||||
}
|
||||
|
||||
.table-cell {
|
||||
padding: 5px;
|
||||
}
|
||||
"""
|
||||
self.html_string = f'<!DOCTYPE html><head><meta charset="utf-8"><title>翻译结果</title><style>{self.css}</style></head>'
|
||||
|
||||
|
||||
def add_row(self, a, b):
|
||||
tmp = """
|
||||
<div class="row table-row">
|
||||
<div class="column table-cell">REPLACE_A</div>
|
||||
<div class="column table-cell">REPLACE_B</div>
|
||||
</div>
|
||||
"""
|
||||
from toolbox import markdown_convertion
|
||||
tmp = tmp.replace('REPLACE_A', markdown_convertion(a))
|
||||
tmp = tmp.replace('REPLACE_B', markdown_convertion(b))
|
||||
self.html_string += tmp
|
||||
|
||||
|
||||
def save_file(self, file_name):
|
||||
with open(os.path.join(get_log_folder(), file_name), 'w', encoding='utf8') as f:
|
||||
f.write(self.html_string.encode('utf-8', 'ignore').decode())
|
||||
return os.path.join(get_log_folder(), file_name)
|
@ -24,10 +24,11 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
||||
try:
|
||||
import fitz
|
||||
import tiktoken
|
||||
import scipdf
|
||||
except:
|
||||
report_execption(chatbot, history,
|
||||
a=f"解析项目: {txt}",
|
||||
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade pymupdf tiktoken```。")
|
||||
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade pymupdf tiktoken scipdf_parser```。")
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
return
|
||||
|
||||
@ -58,7 +59,6 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
|
||||
|
||||
def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url):
|
||||
import copy
|
||||
import tiktoken
|
||||
TOKEN_LIMIT_PER_FRAGMENT = 1280
|
||||
generated_conclusion_files = []
|
||||
generated_html_files = []
|
||||
@ -66,7 +66,7 @@ def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwa
|
||||
for index, fp in enumerate(file_manifest):
|
||||
chatbot.append(["当前进度:", f"正在连接GROBID服务,请稍候: {grobid_url}\n如果等待时间过长,请修改config中的GROBID_URL,可修改成本地GROBID服务。"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
article_dict = parse_pdf(fp, grobid_url)
|
||||
print(article_dict)
|
||||
if article_dict is None: raise RuntimeError("解析PDF失败,请检查PDF是否损坏。")
|
||||
prompt = "以下是一篇学术论文的基本信息:\n"
|
||||
# title
|
||||
title = article_dict.get('title', '无法获取 title'); prompt += f'title:{title}\n\n'
|
||||
|
@ -75,7 +75,11 @@ def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
|
||||
proxies, = get_conf('proxies')
|
||||
urls = google(txt, proxies)
|
||||
history = []
|
||||
|
||||
if len(urls) == 0:
|
||||
chatbot.append((f"结论:{txt}",
|
||||
"[Local Message] 受到google限制,无法从google获取信息!"))
|
||||
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
|
||||
return
|
||||
# ------------- < 第2步:依次访问网页 > -------------
|
||||
max_search_result = 5 # 最多收纳多少个网页的结果
|
||||
for index, url in enumerate(urls[:max_search_result]):
|
||||
|
@ -75,7 +75,11 @@ def 连接bing搜索回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, histor
|
||||
proxies, = get_conf('proxies')
|
||||
urls = bing_search(txt, proxies)
|
||||
history = []
|
||||
|
||||
if len(urls) == 0:
|
||||
chatbot.append((f"结论:{txt}",
|
||||
"[Local Message] 受到bing限制,无法从bing获取信息!"))
|
||||
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
|
||||
return
|
||||
# ------------- < 第2步:依次访问网页 > -------------
|
||||
max_search_result = 8 # 最多收纳多少个网页的结果
|
||||
for index, url in enumerate(urls[:max_search_result]):
|
||||
|
@ -1,24 +1,68 @@
|
||||
"""
|
||||
Explanation of the Void Terminal Plugin:
|
||||
|
||||
Please describe in natural language what you want to do.
|
||||
|
||||
1. You can open the plugin's dropdown menu to explore various capabilities of this project, and then describe your needs in natural language, for example:
|
||||
- "Please call the plugin to translate a PDF paper for me. I just uploaded the paper to the upload area."
|
||||
- "Please use the plugin to translate a PDF paper, with the address being https://www.nature.com/articles/s41586-019-1724-z.pdf."
|
||||
- "Generate an image with blooming flowers and lush green grass using the plugin."
|
||||
- "Translate the README using the plugin. The GitHub URL is https://github.com/facebookresearch/co-tracker."
|
||||
- "Translate an Arxiv paper for me. The Arxiv ID is 1812.10695. Remember to use the plugin and don't do it manually!"
|
||||
- "I don't like the current interface color. Modify the configuration and change the theme to THEME="High-Contrast"."
|
||||
- "Could you please explain the structure of the Transformer network?"
|
||||
|
||||
2. If you use keywords like "call the plugin xxx", "modify the configuration xxx", "please", etc., your intention can be recognized more accurately.
|
||||
|
||||
3. Your intention can be recognized more accurately when using powerful models like GPT4. This plugin is relatively new, so please feel free to provide feedback on GitHub.
|
||||
|
||||
4. Now, if you need to process a file, please upload the file (drag the file to the file upload area) or describe the path to the file.
|
||||
|
||||
5. If you don't need to upload a file, you can simply repeat your command again.
|
||||
"""
|
||||
explain_msg = """
|
||||
## 虚空终端插件说明:
|
||||
|
||||
1. 请用**自然语言**描述您需要做什么。例如:
|
||||
- 「请调用插件,为我翻译PDF论文,论文我刚刚放到上传区了」
|
||||
- 「请调用插件翻译PDF论文,地址为https://aaa/bbb/ccc.pdf」
|
||||
- 「把Arxiv论文翻译成中文PDF,arxiv论文的ID是1812.10695,记得用插件!」
|
||||
- 「生成一张图片,图中鲜花怒放,绿草如茵,用插件实现」
|
||||
- 「用插件翻译README,Github网址是https://github.com/facebookresearch/co-tracker」
|
||||
- 「我不喜欢当前的界面颜色,修改配置,把主题THEME更换为THEME="High-Contrast"」
|
||||
- 「请问Transformer网络的结构是怎样的?」
|
||||
|
||||
2. 您可以打开插件下拉菜单以了解本项目的各种能力。
|
||||
|
||||
3. 如果您使用「调用插件xxx」、「修改配置xxx」、「请问」等关键词,您的意图可以被识别的更准确。
|
||||
|
||||
4. 建议使用 GPT3.5 或更强的模型,弱模型可能无法理解您的想法。该插件诞生时间不长,欢迎您前往Github反馈问题。
|
||||
|
||||
5. 现在,如果需要处理文件,请您上传文件(将文件拖动到文件上传区),或者描述文件所在的路径。
|
||||
|
||||
6. 如果不需要上传文件,现在您只需要再次重复一次您的指令即可。
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import List
|
||||
from toolbox import CatchException, update_ui, gen_time_str
|
||||
from toolbox import update_ui_lastest_msg
|
||||
from toolbox import update_ui_lastest_msg, disable_auto_promotion
|
||||
from request_llm.bridge_all import predict_no_ui_long_connection
|
||||
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
|
||||
from crazy_functions.crazy_utils import input_clipping
|
||||
from crazy_functions.json_fns.pydantic_io import GptJsonIO
|
||||
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
|
||||
from crazy_functions.vt_fns.vt_state import VoidTerminalState
|
||||
from crazy_functions.vt_fns.vt_modify_config import modify_configuration_hot
|
||||
from crazy_functions.vt_fns.vt_modify_config import modify_configuration_reboot
|
||||
from crazy_functions.vt_fns.vt_call_plugin import execute_plugin
|
||||
from enum import Enum
|
||||
import copy, json, pickle, os, sys
|
||||
|
||||
|
||||
class UserIntention(BaseModel):
|
||||
user_prompt: str = Field(description="the content of user input", default="")
|
||||
intention_type: str = Field(description="the type of user intention, choose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']", default="Chat")
|
||||
intention_type: str = Field(description="the type of user intention, choose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']", default="ExecutePlugin")
|
||||
user_provide_file: bool = Field(description="whether the user provides a path to a file", default=False)
|
||||
user_provide_url: bool = Field(description="whether the user provides a url", default=False)
|
||||
|
||||
|
||||
def chat(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
|
||||
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
inputs=txt, inputs_show_user=txt,
|
||||
@ -30,12 +74,24 @@ def chat(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_i
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
pass
|
||||
|
||||
def analyze_with_rule(txt):
|
||||
|
||||
explain_intention_to_user = {
|
||||
'Chat': "聊天对话",
|
||||
'ExecutePlugin': "调用插件",
|
||||
'ModifyConfiguration': "修改配置",
|
||||
}
|
||||
|
||||
|
||||
def analyze_intention_with_simple_rules(txt):
|
||||
user_intention = UserIntention()
|
||||
user_intention.user_prompt = txt
|
||||
is_certain = False
|
||||
|
||||
if '调用插件' in txt:
|
||||
if '请问' in txt:
|
||||
is_certain = True
|
||||
user_intention.intention_type = 'Chat'
|
||||
|
||||
if '用插件' in txt:
|
||||
is_certain = True
|
||||
user_intention.intention_type = 'ExecutePlugin'
|
||||
|
||||
@ -45,43 +101,68 @@ def analyze_with_rule(txt):
|
||||
|
||||
return is_certain, user_intention
|
||||
|
||||
|
||||
@CatchException
|
||||
def 自动终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
"""
|
||||
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
|
||||
llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行
|
||||
plugin_kwargs 插件模型的参数, 如温度和top_p等, 一般原样传递下去就行
|
||||
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(("自动终端状态: ", f"正在执行任务: {txt}"))
|
||||
def 虚空终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
disable_auto_promotion(chatbot=chatbot)
|
||||
# 获取当前虚空终端状态
|
||||
state = VoidTerminalState.get_state(chatbot)
|
||||
appendix_msg = ""
|
||||
|
||||
# 用简单的关键词检测用户意图
|
||||
is_certain, _ = analyze_intention_with_simple_rules(txt)
|
||||
if txt.startswith('private_upload/') and len(txt) == 34:
|
||||
state.set_state(chatbot=chatbot, key='has_provided_explaination', value=False)
|
||||
appendix_msg = "\n\n**很好,您已经上传了文件**,现在请您描述您的需求。"
|
||||
|
||||
if is_certain or (state.has_provided_explaination):
|
||||
# 如果意图明确,跳过提示环节
|
||||
state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
|
||||
state.unlock_plugin(chatbot=chatbot)
|
||||
yield from update_ui(chatbot=chatbot, history=history)
|
||||
yield from 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
|
||||
return
|
||||
else:
|
||||
# 如果意图模糊,提示
|
||||
state.set_state(chatbot=chatbot, key='has_provided_explaination', value=True)
|
||||
state.lock_plugin(chatbot=chatbot)
|
||||
chatbot.append(("虚空终端状态:", explain_msg+appendix_msg))
|
||||
yield from update_ui(chatbot=chatbot, history=history)
|
||||
return
|
||||
|
||||
|
||||
|
||||
def 虚空终端主路由(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
|
||||
history = []
|
||||
chatbot.append(("虚空终端状态: ", f"正在执行任务: {txt}"))
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
# 初始化插件状态
|
||||
state = chatbot._cookies.get('plugin_state', None)
|
||||
if state is not None: state = pickle.loads(state)
|
||||
else: state = {}
|
||||
|
||||
def update_vt_state():
|
||||
# 赋予插件锁定 锁定插件回调路径,当下一次用户提交时,会直接转到该函数
|
||||
chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->自动终端'
|
||||
chatbot._cookies['vt_state'] = pickle.dumps(state)
|
||||
|
||||
# ⭐ ⭐ ⭐ 分析用户意图
|
||||
is_certain, user_intention = analyze_with_rule(txt)
|
||||
is_certain, user_intention = analyze_intention_with_simple_rules(txt)
|
||||
if not is_certain:
|
||||
yield from update_ui_lastest_msg(lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
|
||||
yield from update_ui_lastest_msg(
|
||||
lastmsg=f"正在执行任务: {txt}\n\n分析用户意图中", chatbot=chatbot, history=history, delay=0)
|
||||
gpt_json_io = GptJsonIO(UserIntention)
|
||||
inputs = "Analyze the intention of the user according to following user input: \n\n" + txt + '\n\n' + gpt_json_io.format_instructions
|
||||
rf_req = "\nchoose from ['ModifyConfiguration', 'ExecutePlugin', 'Chat']"
|
||||
inputs = "Analyze the intention of the user according to following user input: \n\n" + \
|
||||
">> " + (txt+rf_req).rstrip('\n').replace('\n','\n>> ') + '\n\n' + gpt_json_io.format_instructions
|
||||
run_gpt_fn = lambda inputs, sys_prompt: predict_no_ui_long_connection(
|
||||
inputs=inputs, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=[])
|
||||
user_intention = gpt_json_io.generate_output_auto_repair(run_gpt_fn(inputs, ""), run_gpt_fn)
|
||||
analyze_res = run_gpt_fn(inputs, "")
|
||||
try:
|
||||
user_intention = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn)
|
||||
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
|
||||
except JsonStringError as e:
|
||||
yield from update_ui_lastest_msg(
|
||||
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 失败 当前语言模型({llm_kwargs['llm_model']})不能理解您的意图", chatbot=chatbot, history=history, delay=0)
|
||||
return
|
||||
else:
|
||||
pass
|
||||
|
||||
yield from update_ui_lastest_msg(
|
||||
lastmsg=f"正在执行任务: {txt}\n\n用户意图理解: 意图={explain_intention_to_user[user_intention.intention_type]}",
|
||||
chatbot=chatbot, history=history, delay=0)
|
||||
|
||||
# 用户意图: 修改本项目的配置
|
||||
if user_intention.intention_type == 'ModifyConfiguration':
|
||||
yield from modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention)
|
||||
@ -96,23 +177,3 @@ def 自动终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
|
||||
|
||||
return
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
# # if state == 'wait_user_keyword':
|
||||
# # chatbot._cookies['lock_plugin'] = None # 解除插件锁定,避免遗忘导致死锁
|
||||
# # chatbot._cookies['plugin_state_0001'] = None # 解除插件状态,避免遗忘导致死锁
|
||||
|
||||
# # # 解除插件锁定
|
||||
# # chatbot.append((f"获取关键词:{txt}", ""))
|
||||
# # yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
# # inputs=inputs_show_user=f"Extract all image urls in this html page, pick the first 5 images and show them with markdown format: \n\n {page_return}"
|
||||
# # gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
|
||||
# # inputs=inputs, inputs_show_user=inputs_show_user,
|
||||
# # llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
|
||||
# # sys_prompt="When you want to show an image, use markdown format. e.g. . If there are no image url provided, answer 'no image url provided'"
|
||||
# # )
|
||||
# # chatbot[-1] = [chatbot[-1][0], gpt_say]
|
||||
# yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
# return
|
||||
|
@ -80,9 +80,9 @@ class InterviewAssistant(AliyunASR):
|
||||
def __init__(self):
|
||||
self.capture_interval = 0.5 # second
|
||||
self.stop = False
|
||||
self.parsed_text = ""
|
||||
self.parsed_sentence = ""
|
||||
self.buffered_sentence = ""
|
||||
self.parsed_text = "" # 下个句子中已经说完的部分, 由 test_on_result_chg() 写入
|
||||
self.parsed_sentence = "" # 某段话的整个句子,由 test_on_sentence_end() 写入
|
||||
self.buffered_sentence = "" #
|
||||
self.event_on_result_chg = threading.Event()
|
||||
self.event_on_entence_end = threading.Event()
|
||||
self.event_on_commit_question = threading.Event()
|
||||
@ -132,7 +132,7 @@ class InterviewAssistant(AliyunASR):
|
||||
self.plugin_wd.feed()
|
||||
|
||||
if self.event_on_result_chg.is_set():
|
||||
# update audio decode result
|
||||
# called when some words have finished
|
||||
self.event_on_result_chg.clear()
|
||||
chatbot[-1] = list(chatbot[-1])
|
||||
chatbot[-1][0] = self.buffered_sentence + self.parsed_text
|
||||
@ -144,7 +144,11 @@ class InterviewAssistant(AliyunASR):
|
||||
# called when a sentence has ended
|
||||
self.event_on_entence_end.clear()
|
||||
self.parsed_text = self.parsed_sentence
|
||||
self.buffered_sentence += self.parsed_sentence
|
||||
self.buffered_sentence += self.parsed_text
|
||||
chatbot[-1] = list(chatbot[-1])
|
||||
chatbot[-1][0] = self.buffered_sentence
|
||||
history = chatbot2history(chatbot)
|
||||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||||
|
||||
if self.event_on_commit_question.is_set():
|
||||
# called when a question should be commited
|
||||
|
@ -1,7 +1,7 @@
|
||||
#【请修改完参数后,删除此行】请在以下方案中选择一种,然后删除其他的方案,最后docker-compose up运行 | Please choose from one of these options below, delete other options as well as This Line
|
||||
|
||||
## ===================================================
|
||||
## 【方案一】 如果不需要运行本地模型(仅chatgpt,newbing类远程服务)
|
||||
## 【方案一】 如果不需要运行本地模型(仅 chatgpt, azure, 星火, 千帆, claude 等在线大模型服务)
|
||||
## ===================================================
|
||||
version: '3'
|
||||
services:
|
||||
@ -13,7 +13,7 @@ services:
|
||||
USE_PROXY: ' True '
|
||||
proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
|
||||
LLM_MODEL: ' gpt-3.5-turbo '
|
||||
AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "newbing"] '
|
||||
AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "sparkv2", "qianfan"] '
|
||||
WEB_PORT: ' 22303 '
|
||||
ADD_WAIFU: ' True '
|
||||
# THEME: ' Chuanhu-Small-and-Beautiful '
|
||||
|
@ -1,62 +1,2 @@
|
||||
# How to build | 如何构建: docker build -t gpt-academic --network=host -f Dockerfile+ChatGLM .
|
||||
# How to run | (1) 我想直接一键运行(选择0号GPU): docker run --rm -it --net=host --gpus \"device=0\" gpt-academic
|
||||
# How to run | (2) 我想运行之前进容器做一些调整(选择1号GPU): docker run --rm -it --net=host --gpus \"device=1\" gpt-academic bash
|
||||
|
||||
# 从NVIDIA源,从而支持显卡运损(检查宿主的nvidia-smi中的cuda版本必须>=11.3)
|
||||
FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
|
||||
ARG useProxyNetwork=''
|
||||
RUN apt-get update
|
||||
RUN apt-get install -y curl proxychains curl
|
||||
RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
|
||||
# 此Dockerfile不再维护,请前往docs/GithubAction+ChatGLM+Moss
|
||||
|
||||
# 配置代理网络(构建Docker镜像时使用)
|
||||
# # comment out below if you do not need proxy network | 如果不需要翻墙 - 从此行向下删除
|
||||
RUN $useProxyNetwork curl cip.cc
|
||||
RUN sed -i '$ d' /etc/proxychains.conf
|
||||
RUN sed -i '$ d' /etc/proxychains.conf
|
||||
# 在这里填写主机的代理协议(用于从github拉取代码)
|
||||
RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
|
||||
ARG useProxyNetwork=proxychains
|
||||
# # comment out above if you do not need proxy network | 如果不需要翻墙 - 从此行向上删除
|
||||
|
||||
|
||||
# use python3 as the system default python
|
||||
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
|
||||
# 下载pytorch
|
||||
RUN $useProxyNetwork python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
|
||||
# 下载分支
|
||||
WORKDIR /gpt
|
||||
RUN $useProxyNetwork git clone https://github.com/binary-husky/gpt_academic.git
|
||||
WORKDIR /gpt/gpt_academic
|
||||
RUN $useProxyNetwork python3 -m pip install -r requirements.txt
|
||||
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
|
||||
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_newbing.txt
|
||||
|
||||
# 预热CHATGLM参数(非必要 可选步骤)
|
||||
RUN echo ' \n\
|
||||
from transformers import AutoModel, AutoTokenizer \n\
|
||||
chatglm_tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) \n\
|
||||
chatglm_model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).float() ' >> warm_up_chatglm.py
|
||||
RUN python3 -u warm_up_chatglm.py
|
||||
|
||||
# 禁用缓存,确保更新代码
|
||||
ADD "https://www.random.org/cgi-bin/randbyte?nbytes=10&format=h" skipcache
|
||||
RUN $useProxyNetwork git pull
|
||||
|
||||
# 预热Tiktoken模块
|
||||
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
|
||||
|
||||
# 为chatgpt-academic配置代理和API-KEY (非必要 可选步骤)
|
||||
# 可同时填写多个API-KEY,支持openai的key和api2d的key共存,用英文逗号分割,例如API_KEY = "sk-openaikey1,fkxxxx-api2dkey2,........"
|
||||
# LLM_MODEL 是选择初始的模型
|
||||
# LOCAL_MODEL_DEVICE 是选择chatglm等本地模型运行的设备,可选 cpu 和 cuda
|
||||
# [说明: 以下内容与`config.py`一一对应,请查阅config.py来完成一下配置的填写]
|
||||
RUN echo ' \n\
|
||||
API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
|
||||
USE_PROXY = True \n\
|
||||
LLM_MODEL = "chatglm" \n\
|
||||
LOCAL_MODEL_DEVICE = "cuda" \n\
|
||||
proxies = { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } ' >> config_private.py
|
||||
|
||||
# 启动
|
||||
CMD ["python3", "-u", "main.py"]
|
||||
|
@ -1,59 +1 @@
|
||||
# How to build | 如何构建: docker build -t gpt-academic-jittor --network=host -f Dockerfile+ChatGLM .
|
||||
# How to run | (1) 我想直接一键运行(选择0号GPU): docker run --rm -it --net=host --gpus \"device=0\" gpt-academic-jittor bash
|
||||
# How to run | (2) 我想运行之前进容器做一些调整(选择1号GPU): docker run --rm -it --net=host --gpus \"device=1\" gpt-academic-jittor bash
|
||||
|
||||
# 从NVIDIA源,从而支持显卡运损(检查宿主的nvidia-smi中的cuda版本必须>=11.3)
|
||||
FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
|
||||
ARG useProxyNetwork=''
|
||||
RUN apt-get update
|
||||
RUN apt-get install -y curl proxychains curl g++
|
||||
RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
|
||||
|
||||
# 配置代理网络(构建Docker镜像时使用)
|
||||
# # comment out below if you do not need proxy network | 如果不需要翻墙 - 从此行向下删除
|
||||
RUN $useProxyNetwork curl cip.cc
|
||||
RUN sed -i '$ d' /etc/proxychains.conf
|
||||
RUN sed -i '$ d' /etc/proxychains.conf
|
||||
# 在这里填写主机的代理协议(用于从github拉取代码)
|
||||
RUN echo "socks5 127.0.0.1 10880" >> /etc/proxychains.conf
|
||||
ARG useProxyNetwork=proxychains
|
||||
# # comment out above if you do not need proxy network | 如果不需要翻墙 - 从此行向上删除
|
||||
|
||||
|
||||
# use python3 as the system default python
|
||||
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
|
||||
# 下载pytorch
|
||||
RUN $useProxyNetwork python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
|
||||
# 下载分支
|
||||
WORKDIR /gpt
|
||||
RUN $useProxyNetwork git clone https://github.com/binary-husky/gpt_academic.git
|
||||
WORKDIR /gpt/gpt_academic
|
||||
RUN $useProxyNetwork python3 -m pip install -r requirements.txt
|
||||
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_chatglm.txt
|
||||
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_newbing.txt
|
||||
RUN $useProxyNetwork python3 -m pip install -r request_llm/requirements_jittorllms.txt -i https://pypi.jittor.org/simple -I
|
||||
|
||||
# 下载JittorLLMs
|
||||
RUN $useProxyNetwork git clone https://github.com/binary-husky/JittorLLMs.git --depth 1 request_llm/jittorllms
|
||||
|
||||
# 禁用缓存,确保更新代码
|
||||
ADD "https://www.random.org/cgi-bin/randbyte?nbytes=10&format=h" skipcache
|
||||
RUN $useProxyNetwork git pull
|
||||
|
||||
# 预热Tiktoken模块
|
||||
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
|
||||
|
||||
# 为chatgpt-academic配置代理和API-KEY (非必要 可选步骤)
|
||||
# 可同时填写多个API-KEY,支持openai的key和api2d的key共存,用英文逗号分割,例如API_KEY = "sk-openaikey1,fkxxxx-api2dkey2,........"
|
||||
# LLM_MODEL 是选择初始的模型
|
||||
# LOCAL_MODEL_DEVICE 是选择chatglm等本地模型运行的设备,可选 cpu 和 cuda
|
||||
# [说明: 以下内容与`config.py`一一对应,请查阅config.py来完成一下配置的填写]
|
||||
RUN echo ' \n\
|
||||
API_KEY = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \n\
|
||||
USE_PROXY = True \n\
|
||||
LLM_MODEL = "chatglm" \n\
|
||||
LOCAL_MODEL_DEVICE = "cuda" \n\
|
||||
proxies = { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } ' >> config_private.py
|
||||
|
||||
# 启动
|
||||
CMD ["python3", "-u", "main.py"]
|
||||
# 此Dockerfile不再维护,请前往docs/GithubAction+JittorLLMs
|
@ -1,27 +1 @@
|
||||
# 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"]
|
||||
# 此Dockerfile不再维护,请前往docs/GithubAction+NoLocal+Latex
|
||||
|
35
docs/GithubAction+AllCapacity
Normal file
35
docs/GithubAction+AllCapacity
Normal file
@ -0,0 +1,35 @@
|
||||
# docker build -t gpt-academic-all-capacity -f docs/GithubAction+AllCapacity --network=host --build-arg http_proxy=http://localhost:10881 --build-arg https_proxy=http://localhost:10881 .
|
||||
|
||||
# 从NVIDIA源,从而支持显卡(检查宿主的nvidia-smi中的cuda版本必须>=11.3)
|
||||
FROM fuqingxu/11.3.1-runtime-ubuntu20.04-with-texlive:latest
|
||||
|
||||
# use python3 as the system default python
|
||||
WORKDIR /gpt
|
||||
RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8
|
||||
# 下载pytorch
|
||||
RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113
|
||||
# 下载分支
|
||||
WORKDIR /gpt
|
||||
RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
|
||||
WORKDIR /gpt/gpt_academic
|
||||
RUN git clone https://github.com/OpenLMLab/MOSS.git request_llm/moss
|
||||
RUN python3 -m pip install openai numpy arxiv rich
|
||||
RUN python3 -m pip install colorama Markdown pygments pymupdf
|
||||
RUN python3 -m pip install python-docx moviepy pdfminer
|
||||
RUN python3 -m pip install zh_langchain==0.2.1
|
||||
RUN python3 -m pip install nougat-ocr
|
||||
RUN python3 -m pip install rarfile py7zr manim manimgl
|
||||
RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
|
||||
RUN python3 -m pip install -r requirements.txt
|
||||
RUN python3 -m pip install -r request_llm/requirements_moss.txt
|
||||
RUN python3 -m pip install -r request_llm/requirements_qwen.txt
|
||||
RUN python3 -m pip install -r request_llm/requirements_chatglm.txt
|
||||
RUN python3 -m pip install -r request_llm/requirements_newbing.txt
|
||||
|
||||
|
||||
|
||||
# 预热Tiktoken模块
|
||||
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
|
||||
|
||||
# 启动
|
||||
CMD ["python3", "-u", "main.py"]
|
@ -1,7 +1,6 @@
|
||||
|
||||
# 从NVIDIA源,从而支持显卡运损(检查宿主的nvidia-smi中的cuda版本必须>=11.3)
|
||||
FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04
|
||||
ARG useProxyNetwork=''
|
||||
RUN apt-get update
|
||||
RUN apt-get install -y curl proxychains curl gcc
|
||||
RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing
|
||||
|
@ -1,6 +1,6 @@
|
||||
# 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 .
|
||||
# - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/GithubAction+NoLocal+Latex .
|
||||
# - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
|
||||
|
||||
FROM fuqingxu/python311_texlive_ctex:latest
|
||||
@ -10,6 +10,10 @@ WORKDIR /gpt
|
||||
|
||||
RUN pip3 install gradio openai numpy arxiv rich
|
||||
RUN pip3 install colorama Markdown pygments pymupdf
|
||||
RUN pip3 install python-docx moviepy pdfminer
|
||||
RUN pip3 install zh_langchain==0.2.1
|
||||
RUN pip3 install nougat-ocr
|
||||
RUN pip3 install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
|
||||
|
||||
# 装载项目文件
|
||||
COPY . .
|
||||
|
@ -2161,5 +2161,292 @@
|
||||
"在运行过程中动态地修改配置": "Dynamically modify configurations during runtime",
|
||||
"请先把模型切换至gpt-*或者api2d-*": "Please switch the model to gpt-* or api2d-* first",
|
||||
"获取简单聊天的句柄": "Get handle of simple chat",
|
||||
"获取插件的默认参数": "Get default parameters of plugin"
|
||||
"获取插件的默认参数": "Get default parameters of plugin",
|
||||
"GROBID服务不可用": "GROBID service is unavailable",
|
||||
"请问": "May I ask",
|
||||
"如果等待时间过长": "If the waiting time is too long",
|
||||
"编程": "programming",
|
||||
"5. 现在": "5. Now",
|
||||
"您不必读这个else分支": "You don't have to read this else branch",
|
||||
"用插件实现": "Implement with plugins",
|
||||
"插件分类默认选项": "Default options for plugin classification",
|
||||
"填写多个可以均衡负载": "Filling in multiple can balance the load",
|
||||
"色彩主题": "Color theme",
|
||||
"可能附带额外依赖 -=-=-=-=-=-=-": "May come with additional dependencies -=-=-=-=-=-=-",
|
||||
"讯飞星火认知大模型": "Xunfei Xinghuo cognitive model",
|
||||
"ParsingLuaProject的所有源文件 | 输入参数为路径": "All source files of ParsingLuaProject | Input parameter is path",
|
||||
"复制以下空间https": "Copy the following space https",
|
||||
"如果意图明确": "If the intention is clear",
|
||||
"如系统是Linux": "If the system is Linux",
|
||||
"├── 语音功能": "├── Voice function",
|
||||
"见Github wiki": "See Github wiki",
|
||||
"⭐ ⭐ ⭐ 立即应用配置": "⭐ ⭐ ⭐ Apply configuration immediately",
|
||||
"现在您只需要再次重复一次您的指令即可": "Now you just need to repeat your command again",
|
||||
"没辙了": "No way",
|
||||
"解析Jupyter Notebook文件 | 输入参数为路径": "Parse Jupyter Notebook file | Input parameter is path",
|
||||
"⭐ ⭐ ⭐ 确认插件参数": "⭐ ⭐ ⭐ Confirm plugin parameters",
|
||||
"找不到合适插件执行该任务": "Cannot find a suitable plugin to perform this task",
|
||||
"接驳VoidTerminal": "Connect to VoidTerminal",
|
||||
"**很好": "**Very good",
|
||||
"对话|编程": "Conversation|Programming",
|
||||
"对话|编程|学术": "Conversation|Programming|Academic",
|
||||
"4. 建议使用 GPT3.5 或更强的模型": "4. It is recommended to use GPT3.5 or a stronger model",
|
||||
"「请调用插件翻译PDF论文": "Please call the plugin to translate the PDF paper",
|
||||
"3. 如果您使用「调用插件xxx」、「修改配置xxx」、「请问」等关键词": "3. If you use keywords such as 'call plugin xxx', 'modify configuration xxx', 'please', etc.",
|
||||
"以下是一篇学术论文的基本信息": "The following is the basic information of an academic paper",
|
||||
"GROBID服务器地址": "GROBID server address",
|
||||
"修改配置": "Modify configuration",
|
||||
"理解PDF文档的内容并进行回答 | 输入参数为路径": "Understand the content of the PDF document and answer | Input parameter is path",
|
||||
"对于需要高级参数的插件": "For plugins that require advanced parameters",
|
||||
"🏃♂️🏃♂️🏃♂️ 主进程执行": "Main process execution 🏃♂️🏃♂️🏃♂️",
|
||||
"没有填写 HUGGINGFACE_ACCESS_TOKEN": "HUGGINGFACE_ACCESS_TOKEN not filled in",
|
||||
"调度插件": "Scheduling plugin",
|
||||
"语言模型": "Language model",
|
||||
"├── ADD_WAIFU 加一个live2d装饰": "├── ADD_WAIFU Add a live2d decoration",
|
||||
"初始化": "Initialization",
|
||||
"选择了不存在的插件": "Selected a non-existent plugin",
|
||||
"修改本项目的配置": "Modify the configuration of this project",
|
||||
"如果输入的文件路径是正确的": "If the input file path is correct",
|
||||
"2. 您可以打开插件下拉菜单以了解本项目的各种能力": "2. You can open the plugin dropdown menu to learn about various capabilities of this project",
|
||||
"VoidTerminal插件说明": "VoidTerminal plugin description",
|
||||
"无法理解您的需求": "Unable to understand your requirements",
|
||||
"默认 AdvancedArgs = False": "Default AdvancedArgs = False",
|
||||
"「请问Transformer网络的结构是怎样的": "What is the structure of the Transformer network?",
|
||||
"比如1812.10695": "For example, 1812.10695",
|
||||
"翻译README或MD": "Translate README or MD",
|
||||
"读取新配置中": "Reading new configuration",
|
||||
"假如偏离了您的要求": "If it deviates from your requirements",
|
||||
"├── THEME 色彩主题": "├── THEME color theme",
|
||||
"如果还找不到": "If still not found",
|
||||
"问": "Ask",
|
||||
"请检查系统字体": "Please check system fonts",
|
||||
"如果错误": "If there is an error",
|
||||
"作为替代": "As an alternative",
|
||||
"ParseJavaProject的所有源文件 | 输入参数为路径": "All source files of ParseJavaProject | Input parameter is path",
|
||||
"比对相同参数时生成的url与自己代码生成的url是否一致": "Check if the generated URL matches the one generated by your code when comparing the same parameters",
|
||||
"清除本地缓存数据": "Clear local cache data",
|
||||
"使用谷歌学术检索助手搜索指定URL的结果 | 输入参数为谷歌学术搜索页的URL": "Use Google Scholar search assistant to search for results of a specific URL | Input parameter is the URL of Google Scholar search page",
|
||||
"运行方法": "Running method",
|
||||
"您已经上传了文件**": "You have uploaded the file **",
|
||||
"「给爷翻译Arxiv论文": "Translate Arxiv papers for me",
|
||||
"请修改config中的GROBID_URL": "Please modify GROBID_URL in the config",
|
||||
"处理特殊情况": "Handling special cases",
|
||||
"不要自己瞎搞!」": "Don't mess around by yourself!",
|
||||
"LoadConversationHistoryArchive | 输入参数为路径": "LoadConversationHistoryArchive | Input parameter is a path",
|
||||
"| 输入参数是一个问题": "| Input parameter is a question",
|
||||
"├── CHATBOT_HEIGHT 对话窗的高度": "├── CHATBOT_HEIGHT Height of the chat window",
|
||||
"对C": "To C",
|
||||
"默认关闭": "Default closed",
|
||||
"当前进度": "Current progress",
|
||||
"HUGGINGFACE的TOKEN": "HUGGINGFACE's TOKEN",
|
||||
"查找可用插件中": "Searching for available plugins",
|
||||
"下载LLAMA时起作用 https": "Works when downloading LLAMA https",
|
||||
"使用 AK": "Using AK",
|
||||
"正在执行任务": "Executing task",
|
||||
"保存当前的对话 | 不需要输入参数": "Save current conversation | No input parameters required",
|
||||
"对话": "Conversation",
|
||||
"图中鲜花怒放": "Flowers blooming in the picture",
|
||||
"批量将Markdown文件中文翻译为英文 | 输入参数为路径或上传压缩包": "Batch translate Chinese to English in Markdown files | Input parameter is a path or upload a compressed package",
|
||||
"ParsingCSharpProject的所有源文件 | 输入参数为路径": "ParsingCSharpProject's all source files | Input parameter is a path",
|
||||
"为我翻译PDF论文": "Translate PDF papers for me",
|
||||
"聊天对话": "Chat conversation",
|
||||
"拼接鉴权参数": "Concatenate authentication parameters",
|
||||
"请检查config中的GROBID_URL": "Please check the GROBID_URL in the config",
|
||||
"拼接字符串": "Concatenate strings",
|
||||
"您的意图可以被识别的更准确": "Your intent can be recognized more accurately",
|
||||
"该模型有七个 bin 文件": "The model has seven bin files",
|
||||
"但思路相同": "But the idea is the same",
|
||||
"你需要翻译": "You need to translate",
|
||||
"或者描述文件所在的路径": "Or the path of the description file",
|
||||
"请您上传文件": "Please upload the file",
|
||||
"不常用": "Not commonly used",
|
||||
"尚未充分测试的实验性插件 & 需要额外依赖的插件 -=--=-": "Experimental plugins that have not been fully tested & plugins that require additional dependencies -=--=-",
|
||||
"⭐ ⭐ ⭐ 选择插件": "⭐ ⭐ ⭐ Select plugin",
|
||||
"当前配置不允许被修改!如需激活本功能": "The current configuration does not allow modification! To activate this feature",
|
||||
"正在连接GROBID服务": "Connecting to GROBID service",
|
||||
"用户图形界面布局依赖关系示意图": "Diagram of user interface layout dependencies",
|
||||
"是否允许通过自然语言描述修改本页的配置": "Allow modifying the configuration of this page through natural language description",
|
||||
"self.chatbot被序列化": "self.chatbot is serialized",
|
||||
"本地Latex论文精细翻译 | 输入参数是路径": "Locally translate Latex papers with fine-grained translation | Input parameter is the path",
|
||||
"抱歉": "Sorry",
|
||||
"以下这部分是最早加入的最稳定的模型 -=-=-=-=-=-=-": "The following section is the earliest and most stable model added",
|
||||
"「用插件翻译README": "Translate README with plugins",
|
||||
"如果不正确": "If incorrect",
|
||||
"⭐ ⭐ ⭐ 读取可配置项目条目": "⭐ ⭐ ⭐ Read configurable project entries",
|
||||
"开始语言对话 | 没有输入参数": "Start language conversation | No input parameters",
|
||||
"谨慎操作 | 不需要输入参数": "Handle with caution | No input parameters required",
|
||||
"对英文Latex项目全文进行纠错处理 | 输入参数为路径或上传压缩包": "Correct the entire English Latex project | Input parameter is the path or upload compressed package",
|
||||
"如果需要处理文件": "If file processing is required",
|
||||
"提供图像的内容": "Provide the content of the image",
|
||||
"查看历史上的今天事件 | 不需要输入参数": "View historical events of today | No input parameters required",
|
||||
"这个稍微啰嗦一点": "This is a bit verbose",
|
||||
"多线程解析并翻译此项目的源码 | 不需要输入参数": "Parse and translate the source code of this project in multi-threading | No input parameters required",
|
||||
"此处打印出建立连接时候的url": "Print the URL when establishing the connection here",
|
||||
"精准翻译PDF论文为中文 | 输入参数为路径": "Translate PDF papers accurately into Chinese | Input parameter is the path",
|
||||
"检测到操作错误!当您上传文档之后": "Operation error detected! After you upload the document",
|
||||
"在线大模型配置关联关系示意图": "Online large model configuration relationship diagram",
|
||||
"你的填写的空间名如grobid": "Your filled space name such as grobid",
|
||||
"获取方法": "Get method",
|
||||
"| 输入参数为路径": "| Input parameter is the path",
|
||||
"⭐ ⭐ ⭐ 执行插件": "⭐ ⭐ ⭐ Execute plugin",
|
||||
"├── ALLOW_RESET_CONFIG 是否允许通过自然语言描述修改本页的配置": "├── ALLOW_RESET_CONFIG Whether to allow modifying the configuration of this page through natural language description",
|
||||
"重新页面即可生效": "Refresh the page to take effect",
|
||||
"设为public": "Set as public",
|
||||
"并在此处指定模型路径": "And specify the model path here",
|
||||
"分析用户意图中": "Analyzing user intent",
|
||||
"刷新下拉列表": "Refresh the drop-down list",
|
||||
"失败 当前语言模型": "Failed current language model",
|
||||
"1. 请用**自然语言**描述您需要做什么": "1. Please describe what you need to do in **natural language**",
|
||||
"对Latex项目全文进行中译英处理 | 输入参数为路径或上传压缩包": "Translate the full text of Latex projects from Chinese to English | Input parameter is the path or upload a compressed package",
|
||||
"没有配置BAIDU_CLOUD_API_KEY": "No configuration for BAIDU_CLOUD_API_KEY",
|
||||
"设置默认值": "Set default value",
|
||||
"如果太多了会导致gpt无法理解": "If there are too many, it will cause GPT to be unable to understand",
|
||||
"绿草如茵": "Green grass",
|
||||
"├── LAYOUT 窗口布局": "├── LAYOUT window layout",
|
||||
"用户意图理解": "User intent understanding",
|
||||
"生成RFC1123格式的时间戳": "Generate RFC1123 formatted timestamp",
|
||||
"欢迎您前往Github反馈问题": "Welcome to go to Github to provide feedback",
|
||||
"排除已经是按钮的插件": "Exclude plugins that are already buttons",
|
||||
"亦在下拉菜单中显示": "Also displayed in the dropdown menu",
|
||||
"导致无法反序列化": "Causing deserialization failure",
|
||||
"意图=": "Intent =",
|
||||
"章节": "Chapter",
|
||||
"调用插件": "Invoke plugin",
|
||||
"ParseRustProject的所有源文件 | 输入参数为路径": "All source files of ParseRustProject | Input parameter is path",
|
||||
"需要点击“函数插件区”按钮进行处理": "Need to click the 'Function Plugin Area' button for processing",
|
||||
"默认 AsButton = True": "Default AsButton = True",
|
||||
"收到websocket错误的处理": "Handling websocket errors",
|
||||
"用插件": "Use Plugin",
|
||||
"没有选择任何插件组": "No plugin group selected",
|
||||
"答": "Answer",
|
||||
"可修改成本地GROBID服务": "Can modify to local GROBID service",
|
||||
"用户意图": "User intent",
|
||||
"对英文Latex项目全文进行润色处理 | 输入参数为路径或上传压缩包": "Polish the full text of English Latex projects | Input parameters are paths or uploaded compressed packages",
|
||||
"「我不喜欢当前的界面颜色": "I don't like the current interface color",
|
||||
"「请调用插件": "Please call the plugin",
|
||||
"VoidTerminal状态": "VoidTerminal status",
|
||||
"新配置": "New configuration",
|
||||
"支持Github链接": "Support Github links",
|
||||
"没有配置BAIDU_CLOUD_SECRET_KEY": "No BAIDU_CLOUD_SECRET_KEY configured",
|
||||
"获取当前VoidTerminal状态": "Get the current VoidTerminal status",
|
||||
"刷新按钮": "Refresh button",
|
||||
"为了防止pickle.dumps": "To prevent pickle.dumps",
|
||||
"放弃治疗": "Give up treatment",
|
||||
"可指定不同的生成长度、top_p等相关超参": "Can specify different generation lengths, top_p and other related hyperparameters",
|
||||
"请将题目和摘要翻译为": "Translate the title and abstract",
|
||||
"通过appid和用户的提问来生成请参数": "Generate request parameters through appid and user's question",
|
||||
"ImageGeneration | 输入参数字符串": "ImageGeneration | Input parameter string",
|
||||
"将文件拖动到文件上传区": "Drag and drop the file to the file upload area",
|
||||
"如果意图模糊": "If the intent is ambiguous",
|
||||
"星火认知大模型": "Spark Cognitive Big Model",
|
||||
"执行中. 删除 gpt_log & private_upload": "Executing. Delete gpt_log & private_upload",
|
||||
"默认 Color = secondary": "Default Color = secondary",
|
||||
"此处也不需要修改": "No modification is needed here",
|
||||
"⭐ ⭐ ⭐ 分析用户意图": "⭐ ⭐ ⭐ Analyze user intent",
|
||||
"再试一次": "Try again",
|
||||
"请写bash命令实现以下功能": "Please write a bash command to implement the following function",
|
||||
"批量SummarizingWordDocuments | 输入参数为路径": "Batch SummarizingWordDocuments | Input parameter is the path",
|
||||
"/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析": "Parse the python file in /Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns",
|
||||
"当我要求你写bash命令时": "When I ask you to write a bash command",
|
||||
"├── AUTO_CLEAR_TXT 是否在提交时自动清空输入框": "├── AUTO_CLEAR_TXT Whether to automatically clear the input box when submitting",
|
||||
"按停止键终止": "Press the stop key to terminate",
|
||||
"文心一言": "Original text",
|
||||
"不能理解您的意图": "Cannot understand your intention",
|
||||
"用简单的关键词检测用户意图": "Detect user intention with simple keywords",
|
||||
"中文": "Chinese",
|
||||
"解析一个C++项目的所有源文件": "Parse all source files of a C++ project",
|
||||
"请求的Prompt为": "Requested prompt is",
|
||||
"参考本demo的时候可取消上方打印的注释": "You can remove the comments above when referring to this demo",
|
||||
"开始接收回复": "Start receiving replies",
|
||||
"接入讯飞星火大模型 https": "Access to Xunfei Xinghuo large model https",
|
||||
"用该压缩包进行反馈": "Use this compressed package for feedback",
|
||||
"翻译Markdown或README": "Translate Markdown or README",
|
||||
"SK 生成鉴权签名": "SK generates authentication signature",
|
||||
"插件参数": "Plugin parameters",
|
||||
"需要访问中文Bing": "Need to access Chinese Bing",
|
||||
"ParseFrontendProject的所有源文件": "Parse all source files of ParseFrontendProject",
|
||||
"现在将执行效果稍差的旧版代码": "Now execute the older version code with slightly worse performance",
|
||||
"您需要明确说明并在指令中提到它": "You need to specify and mention it in the command",
|
||||
"请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件": "Please set ALLOW_RESET_CONFIG=True in config.py and restart the software",
|
||||
"按照自然语言描述生成一个动画 | 输入参数是一段话": "Generate an animation based on natural language description | Input parameter is a sentence",
|
||||
"你的hf用户名如qingxu98": "Your hf username is qingxu98",
|
||||
"Arixv论文精细翻译 | 输入参数arxiv论文的ID": "Fine translation of Arixv paper | Input parameter is the ID of arxiv paper",
|
||||
"无法获取 abstract": "Unable to retrieve abstract",
|
||||
"尽可能地仅用一行命令解决我的要求": "Try to solve my request using only one command",
|
||||
"提取插件参数": "Extract plugin parameters",
|
||||
"配置修改完成": "Configuration modification completed",
|
||||
"正在修改配置中": "Modifying configuration",
|
||||
"ParsePythonProject的所有源文件": "All source files of ParsePythonProject",
|
||||
"请求错误": "Request error",
|
||||
"精准翻译PDF论文": "Accurate translation of PDF paper",
|
||||
"无法获取 authors": "Unable to retrieve authors",
|
||||
"该插件诞生时间不长": "This plugin has not been around for long",
|
||||
"返回项目根路径": "Return project root path",
|
||||
"BatchSummarizePDFDocuments的内容 | 输入参数为路径": "Content of BatchSummarizePDFDocuments | Input parameter is a path",
|
||||
"百度千帆": "Baidu Qianfan",
|
||||
"解析一个C++项目的所有头文件": "Parse all header files of a C++ project",
|
||||
"现在请您描述您的需求": "Now please describe your requirements",
|
||||
"该功能具有一定的危险性": "This feature has a certain level of danger",
|
||||
"收到websocket关闭的处理": "Processing when receiving websocket closure",
|
||||
"读取Tex论文并写摘要 | 输入参数为路径": "Read Tex paper and write abstract | Input parameter is the path",
|
||||
"地址为https": "The address is https",
|
||||
"限制最多前10个配置项": "Limit up to 10 configuration items",
|
||||
"6. 如果不需要上传文件": "6. If file upload is not needed",
|
||||
"默认 Group = 对话": "Default Group = Conversation",
|
||||
"五秒后即将重启!若出现报错请无视即可": "Restarting in five seconds! Please ignore if there is an error",
|
||||
"收到websocket连接建立的处理": "Processing when receiving websocket connection establishment",
|
||||
"批量生成函数的注释 | 输入参数为路径": "Batch generate function comments | Input parameter is the path",
|
||||
"聊天": "Chat",
|
||||
"但您可以尝试再试一次": "But you can try again",
|
||||
"千帆大模型平台": "Qianfan Big Model Platform",
|
||||
"直接运行 python tests/test_plugins.py": "Run python tests/test_plugins.py directly",
|
||||
"或是None": "Or None",
|
||||
"进行hmac-sha256进行加密": "Perform encryption using hmac-sha256",
|
||||
"批量总结音频或视频 | 输入参数为路径": "Batch summarize audio or video | Input parameter is path",
|
||||
"插件在线服务配置依赖关系示意图": "Plugin online service configuration dependency diagram",
|
||||
"开始初始化模型": "Start initializing model",
|
||||
"弱模型可能无法理解您的想法": "Weak model may not understand your ideas",
|
||||
"解除大小写限制": "Remove case sensitivity restriction",
|
||||
"跳过提示环节": "Skip prompt section",
|
||||
"接入一些逆向工程https": "Access some reverse engineering https",
|
||||
"执行完成": "Execution completed",
|
||||
"如果需要配置": "If configuration is needed",
|
||||
"此处不修改;如果使用本地或无地域限制的大模型时": "Do not modify here; if using local or region-unrestricted large models",
|
||||
"你是一个Linux大师级用户": "You are a Linux master-level user",
|
||||
"arxiv论文的ID是1812.10695": "The ID of the arxiv paper is 1812.10695",
|
||||
"而不是点击“提交”按钮": "Instead of clicking the 'Submit' button",
|
||||
"解析一个Go项目的所有源文件 | 输入参数为路径": "Parse all source files of a Go project | Input parameter is path",
|
||||
"对中文Latex项目全文进行润色处理 | 输入参数为路径或上传压缩包": "Polish the entire text of a Chinese Latex project | Input parameter is path or upload compressed package",
|
||||
"「生成一张图片": "Generate an image",
|
||||
"将Markdown或README翻译为中文 | 输入参数为路径或URL": "Translate Markdown or README to Chinese | Input parameters are path or URL",
|
||||
"训练时间": "Training time",
|
||||
"将请求的鉴权参数组合为字典": "Combine the requested authentication parameters into a dictionary",
|
||||
"对Latex项目全文进行英译中处理 | 输入参数为路径或上传压缩包": "Translate the entire text of Latex project from English to Chinese | Input parameters are path or uploaded compressed package",
|
||||
"内容如下": "The content is as follows",
|
||||
"用于高质量地读取PDF文档": "Used for high-quality reading of PDF documents",
|
||||
"上下文太长导致 token 溢出": "The context is too long, causing token overflow",
|
||||
"├── DARK_MODE 暗色模式 / 亮色模式": "├── DARK_MODE Dark mode / Light mode",
|
||||
"语言模型回复为": "The language model replies as",
|
||||
"from crazy_functions.chatglm微调工具 import 微调数据集生成": "from crazy_functions.chatglm fine-tuning tool import fine-tuning dataset generation",
|
||||
"为您选择了插件": "Selected plugin for you",
|
||||
"无法获取 title": "Unable to get title",
|
||||
"收到websocket消息的处理": "Processing of received websocket messages",
|
||||
"2023年": "2023",
|
||||
"清除所有缓存文件": "Clear all cache files",
|
||||
"├── PDF文档精准解析": "├── Accurate parsing of PDF documents",
|
||||
"论文我刚刚放到上传区了": "I just put the paper in the upload area",
|
||||
"生成url": "Generate URL",
|
||||
"以下部分是新加入的模型": "The following section is the newly added model",
|
||||
"学术": "Academic",
|
||||
"├── DEFAULT_FN_GROUPS 插件分类默认选项": "├── DEFAULT_FN_GROUPS Plugin classification default options",
|
||||
"不推荐使用": "Not recommended for use",
|
||||
"正在同时咨询": "Consulting simultaneously",
|
||||
"将Markdown翻译为中文 | 输入参数为路径或URL": "Translate Markdown to Chinese | Input parameters are path or URL",
|
||||
"Github网址是https": "The Github URL is https",
|
||||
"试着加上.tex后缀试试": "Try adding the .tex suffix",
|
||||
"对项目中的各个插件进行测试": "Test each plugin in the project",
|
||||
"插件说明": "Plugin description",
|
||||
"├── CODE_HIGHLIGHT 代码高亮": "├── CODE_HIGHLIGHT Code highlighting",
|
||||
"记得用插件": "Remember to use the plugin",
|
||||
"谨慎操作": "Handle with caution"
|
||||
}
|
@ -83,5 +83,10 @@
|
||||
"图片生成": "ImageGeneration",
|
||||
"动画生成": "AnimationGeneration",
|
||||
"语音助手": "VoiceAssistant",
|
||||
"启动微调": "StartFineTuning"
|
||||
"启动微调": "StartFineTuning",
|
||||
"清除缓存": "ClearCache",
|
||||
"辅助功能": "Accessibility",
|
||||
"虚空终端": "VoidTerminal",
|
||||
"解析PDF_基于GROBID": "ParsePDF_BasedOnGROBID",
|
||||
"虚空终端主路由": "VoidTerminalMainRoute"
|
||||
}
|
74
main.py
74
main.py
@ -6,18 +6,18 @@ def main():
|
||||
from request_llm.bridge_all import predict
|
||||
from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, load_chat_cookies, DummyWith
|
||||
# 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
|
||||
proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT, LAYOUT, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = \
|
||||
get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT', 'LAYOUT', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
|
||||
proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION = get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION')
|
||||
CHATBOT_HEIGHT, LAYOUT, AVAIL_LLM_MODELS, AUTO_CLEAR_TXT = get_conf('CHATBOT_HEIGHT', 'LAYOUT', 'AVAIL_LLM_MODELS', 'AUTO_CLEAR_TXT')
|
||||
ENABLE_AUDIO, AUTO_CLEAR_TXT = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT')
|
||||
|
||||
# 如果WEB_PORT是-1, 则随机选取WEB端口
|
||||
PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
|
||||
if not AUTHENTICATION: AUTHENTICATION = None
|
||||
|
||||
from check_proxy import get_current_version
|
||||
from themes.theme import adjust_theme, advanced_css, theme_declaration
|
||||
initial_prompt = "Serve me as a writing and programming assistant."
|
||||
title_html = f"<h1 align=\"center\">GPT 学术优化 {get_current_version()}</h1>{theme_declaration}"
|
||||
description = """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic),感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
|
||||
description = "代码开源和更新[地址🚀](https://github.com/binary-husky/gpt_academic),"
|
||||
description += "感谢热情的[开发者们❤️](https://github.com/binary-husky/gpt_academic/graphs/contributors)"
|
||||
|
||||
# 问询记录, python 版本建议3.9+(越新越好)
|
||||
import logging, uuid
|
||||
@ -34,7 +34,10 @@ def main():
|
||||
|
||||
# 高级函数插件
|
||||
from crazy_functional import get_crazy_functions
|
||||
crazy_fns = get_crazy_functions()
|
||||
DEFAULT_FN_GROUPS, = get_conf('DEFAULT_FN_GROUPS')
|
||||
plugins = get_crazy_functions()
|
||||
all_plugin_groups = list(set([g for _, plugin in plugins.items() for g in plugin['Group'].split('|')]))
|
||||
match_group = lambda tags, groups: any([g in groups for g in tags.split('|')])
|
||||
|
||||
# 处理markdown文本格式的转变
|
||||
gr.Chatbot.postprocess = format_io
|
||||
@ -83,25 +86,33 @@ def main():
|
||||
if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
|
||||
variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
|
||||
functional[k]["Button"] = gr.Button(k, variant=variant)
|
||||
functional[k]["Button"].style(size="sm")
|
||||
with gr.Accordion("函数插件区", open=True, elem_id="plugin-panel") as area_crazy_fn:
|
||||
with gr.Row():
|
||||
gr.Markdown("插件可读取“输入区”文本/路径作为参数(上传文件自动修正路径)")
|
||||
with gr.Row(elem_id="input-plugin-group"):
|
||||
plugin_group_sel = gr.Dropdown(choices=all_plugin_groups, label='', show_label=False, value=DEFAULT_FN_GROUPS,
|
||||
multiselect=True, interactive=True, elem_classes='normal_mut_select').style(container=False)
|
||||
with gr.Row():
|
||||
for k in crazy_fns:
|
||||
if not crazy_fns[k].get("AsButton", True): continue
|
||||
variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
|
||||
crazy_fns[k]["Button"] = gr.Button(k, variant=variant)
|
||||
crazy_fns[k]["Button"].style(size="sm")
|
||||
for k, plugin in plugins.items():
|
||||
if not plugin.get("AsButton", True): continue
|
||||
visible = True if match_group(plugin['Group'], DEFAULT_FN_GROUPS) else False
|
||||
variant = plugins[k]["Color"] if "Color" in plugin else "secondary"
|
||||
plugin['Button'] = plugins[k]['Button'] = gr.Button(k, variant=variant, visible=visible).style(size="sm")
|
||||
with gr.Row():
|
||||
with gr.Accordion("更多函数插件", open=True):
|
||||
dropdown_fn_list = [k for k in crazy_fns.keys() if not crazy_fns[k].get("AsButton", True)]
|
||||
dropdown_fn_list = []
|
||||
for k, plugin in plugins.items():
|
||||
if not match_group(plugin['Group'], DEFAULT_FN_GROUPS): continue
|
||||
if not plugin.get("AsButton", True): dropdown_fn_list.append(k) # 排除已经是按钮的插件
|
||||
elif plugin.get('AdvancedArgs', False): dropdown_fn_list.append(k) # 对于需要高级参数的插件,亦在下拉菜单中显示
|
||||
with gr.Row():
|
||||
dropdown = gr.Dropdown(dropdown_fn_list, value=r"打开插件列表", label="", show_label=False).style(container=False)
|
||||
with gr.Row():
|
||||
plugin_advanced_arg = gr.Textbox(show_label=True, label="高级参数输入区", visible=False,
|
||||
placeholder="这里是特殊函数插件的高级参数输入区").style(container=False)
|
||||
with gr.Row():
|
||||
switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary")
|
||||
switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary").style(size="sm")
|
||||
with gr.Row():
|
||||
with gr.Accordion("点击展开“文件上传区”。上传本地文件/压缩包供函数插件调用。", open=False) as area_file_up:
|
||||
file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
|
||||
@ -112,7 +123,6 @@ def main():
|
||||
max_length_sl = gr.Slider(minimum=256, maximum=8192, value=4096, step=1, interactive=True, label="Local LLM MaxLength",)
|
||||
checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "底部输入区", "输入清除键", "插件参数区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
|
||||
md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False)
|
||||
|
||||
gr.Markdown(description)
|
||||
with gr.Accordion("备选输入区", open=True, visible=False, elem_id="input-panel2") as area_input_secondary:
|
||||
with gr.Row():
|
||||
@ -123,6 +133,7 @@ def main():
|
||||
resetBtn2 = gr.Button("重置", variant="secondary"); resetBtn2.style(size="sm")
|
||||
stopBtn2 = gr.Button("停止", variant="secondary"); stopBtn2.style(size="sm")
|
||||
clearBtn2 = gr.Button("清除", variant="secondary", visible=False); clearBtn2.style(size="sm")
|
||||
|
||||
# 功能区显示开关与功能区的互动
|
||||
def fn_area_visibility(a):
|
||||
ret = {}
|
||||
@ -160,19 +171,19 @@ def main():
|
||||
click_handle = functional[k]["Button"].click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(k)], outputs=output_combo)
|
||||
cancel_handles.append(click_handle)
|
||||
# 文件上传区,接收文件后与chatbot的互动
|
||||
file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt, txt2, checkboxes], [chatbot, txt, txt2])
|
||||
file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies])
|
||||
# 函数插件-固定按钮区
|
||||
for k in crazy_fns:
|
||||
if not crazy_fns[k].get("AsButton", True): continue
|
||||
click_handle = crazy_fns[k]["Button"].click(ArgsGeneralWrapper(crazy_fns[k]["Function"]), [*input_combo, gr.State(PORT)], output_combo)
|
||||
for k in plugins:
|
||||
if not plugins[k].get("AsButton", True): continue
|
||||
click_handle = plugins[k]["Button"].click(ArgsGeneralWrapper(plugins[k]["Function"]), [*input_combo, gr.State(PORT)], output_combo)
|
||||
click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot])
|
||||
cancel_handles.append(click_handle)
|
||||
# 函数插件-下拉菜单与随变按钮的互动
|
||||
def on_dropdown_changed(k):
|
||||
variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
|
||||
variant = plugins[k]["Color"] if "Color" in plugins[k] else "secondary"
|
||||
ret = {switchy_bt: gr.update(value=k, variant=variant)}
|
||||
if crazy_fns[k].get("AdvancedArgs", False): # 是否唤起高级插件参数区
|
||||
ret.update({plugin_advanced_arg: gr.update(visible=True, label=f"插件[{k}]的高级参数说明:" + crazy_fns[k].get("ArgsReminder", [f"没有提供高级参数功能说明"]))})
|
||||
if plugins[k].get("AdvancedArgs", False): # 是否唤起高级插件参数区
|
||||
ret.update({plugin_advanced_arg: gr.update(visible=True, label=f"插件[{k}]的高级参数说明:" + plugins[k].get("ArgsReminder", [f"没有提供高级参数功能说明"]))})
|
||||
else:
|
||||
ret.update({plugin_advanced_arg: gr.update(visible=False, label=f"插件[{k}]不需要高级参数。")})
|
||||
return ret
|
||||
@ -183,13 +194,26 @@ def main():
|
||||
# 随变按钮的回调函数注册
|
||||
def route(request: gr.Request, k, *args, **kwargs):
|
||||
if k in [r"打开插件列表", r"请先从插件列表中选择"]: return
|
||||
yield from ArgsGeneralWrapper(crazy_fns[k]["Function"])(request, *args, **kwargs)
|
||||
yield from ArgsGeneralWrapper(plugins[k]["Function"])(request, *args, **kwargs)
|
||||
click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
|
||||
click_handle.then(on_report_generated, [cookies, file_upload, chatbot], [cookies, file_upload, chatbot])
|
||||
cancel_handles.append(click_handle)
|
||||
# 终止按钮的回调函数注册
|
||||
stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
|
||||
stopBtn2.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
|
||||
plugins_as_btn = {name:plugin for name, plugin in plugins.items() if plugin.get('Button', None)}
|
||||
def on_group_change(group_list):
|
||||
btn_list = []
|
||||
fns_list = []
|
||||
if not group_list: # 处理特殊情况:没有选择任何插件组
|
||||
return [*[plugin['Button'].update(visible=False) for _, plugin in plugins_as_btn.items()], gr.Dropdown.update(choices=[])]
|
||||
for k, plugin in plugins.items():
|
||||
if plugin.get("AsButton", True):
|
||||
btn_list.append(plugin['Button'].update(visible=match_group(plugin['Group'], group_list))) # 刷新按钮
|
||||
if plugin.get('AdvancedArgs', False): dropdown_fn_list.append(k) # 对于需要高级参数的插件,亦在下拉菜单中显示
|
||||
elif match_group(plugin['Group'], group_list): fns_list.append(k) # 刷新下拉列表
|
||||
return [*btn_list, gr.Dropdown.update(choices=fns_list)]
|
||||
plugin_group_sel.select(fn=on_group_change, inputs=[plugin_group_sel], outputs=[*[plugin['Button'] for name, plugin in plugins_as_btn.items()], dropdown])
|
||||
if ENABLE_AUDIO:
|
||||
from crazy_functions.live_audio.audio_io import RealtimeAudioDistribution
|
||||
rad = RealtimeAudioDistribution()
|
||||
@ -221,8 +245,10 @@ def main():
|
||||
|
||||
auto_opentab_delay()
|
||||
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
|
||||
server_name="0.0.0.0", server_port=PORT,
|
||||
favicon_path="docs/logo.png", auth=AUTHENTICATION,
|
||||
server_name="0.0.0.0",
|
||||
server_port=PORT,
|
||||
favicon_path="docs/logo.png",
|
||||
auth=AUTHENTICATION if len(AUTHENTICATION) != 0 else None,
|
||||
blocked_paths=["config.py","config_private.py","docker-compose.yml","Dockerfile"])
|
||||
|
||||
# 如果需要在二级路径下运行
|
||||
|
@ -478,6 +478,8 @@ def step_2_core_key_translate():
|
||||
up = trans_json(need_translate, language=LANG, special=False)
|
||||
map_to_json(up, language=LANG)
|
||||
cached_translation = read_map_from_json(language=LANG)
|
||||
LANG_STD = 'std'
|
||||
cached_translation.update(read_map_from_json(language=LANG_STD))
|
||||
cached_translation = dict(sorted(cached_translation.items(), key=lambda x: -len(x[0])))
|
||||
|
||||
# ===============================================
|
||||
|
@ -63,9 +63,9 @@ class GetGLMFTHandle(Process):
|
||||
# if not os.path.exists(conf): raise RuntimeError('找不到微调模型信息')
|
||||
# with open(conf, 'r', encoding='utf8') as f:
|
||||
# model_args = json.loads(f.read())
|
||||
ChatGLM_PTUNING_CHECKPOINT, = get_conf('ChatGLM_PTUNING_CHECKPOINT')
|
||||
assert os.path.exists(ChatGLM_PTUNING_CHECKPOINT), "找不到微调模型检查点"
|
||||
conf = os.path.join(ChatGLM_PTUNING_CHECKPOINT, "config.json")
|
||||
CHATGLM_PTUNING_CHECKPOINT, = get_conf('CHATGLM_PTUNING_CHECKPOINT')
|
||||
assert os.path.exists(CHATGLM_PTUNING_CHECKPOINT), "找不到微调模型检查点"
|
||||
conf = os.path.join(CHATGLM_PTUNING_CHECKPOINT, "config.json")
|
||||
with open(conf, 'r', encoding='utf8') as f:
|
||||
model_args = json.loads(f.read())
|
||||
if 'model_name_or_path' not in model_args:
|
||||
@ -78,9 +78,9 @@ class GetGLMFTHandle(Process):
|
||||
config.pre_seq_len = model_args['pre_seq_len']
|
||||
config.prefix_projection = model_args['prefix_projection']
|
||||
|
||||
print(f"Loading prefix_encoder weight from {ChatGLM_PTUNING_CHECKPOINT}")
|
||||
print(f"Loading prefix_encoder weight from {CHATGLM_PTUNING_CHECKPOINT}")
|
||||
model = AutoModel.from_pretrained(model_args['model_name_or_path'], config=config, trust_remote_code=True)
|
||||
prefix_state_dict = torch.load(os.path.join(ChatGLM_PTUNING_CHECKPOINT, "pytorch_model.bin"))
|
||||
prefix_state_dict = torch.load(os.path.join(CHATGLM_PTUNING_CHECKPOINT, "pytorch_model.bin"))
|
||||
new_prefix_state_dict = {}
|
||||
for k, v in prefix_state_dict.items():
|
||||
if k.startswith("transformer.prefix_encoder."):
|
||||
|
@ -49,16 +49,17 @@ def get_access_token():
|
||||
|
||||
def generate_message_payload(inputs, llm_kwargs, history, system_prompt):
|
||||
conversation_cnt = len(history) // 2
|
||||
if system_prompt == "": system_prompt = "Hello"
|
||||
messages = [{"role": "user", "content": system_prompt}]
|
||||
messages.append({"role": "assistant", "content": 'Certainly!'})
|
||||
if conversation_cnt:
|
||||
for index in range(0, 2*conversation_cnt, 2):
|
||||
what_i_have_asked = {}
|
||||
what_i_have_asked["role"] = "user"
|
||||
what_i_have_asked["content"] = history[index]
|
||||
what_i_have_asked["content"] = history[index] if history[index]!="" else "Hello"
|
||||
what_gpt_answer = {}
|
||||
what_gpt_answer["role"] = "assistant"
|
||||
what_gpt_answer["content"] = history[index+1]
|
||||
what_gpt_answer["content"] = history[index+1] if history[index]!="" else "Hello"
|
||||
if what_i_have_asked["content"] != "":
|
||||
if what_gpt_answer["content"] == "": continue
|
||||
if what_gpt_answer["content"] == timeout_bot_msg: continue
|
||||
|
@ -2,11 +2,17 @@
|
||||
import time
|
||||
import threading
|
||||
import importlib
|
||||
from toolbox import update_ui, get_conf
|
||||
from toolbox import update_ui, get_conf, update_ui_lastest_msg
|
||||
from multiprocessing import Process, Pipe
|
||||
|
||||
model_name = '星火认知大模型'
|
||||
|
||||
def validate_key():
|
||||
XFYUN_APPID, = get_conf('XFYUN_APPID', )
|
||||
if XFYUN_APPID == '00000000' or XFYUN_APPID == '':
|
||||
return False
|
||||
return True
|
||||
|
||||
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
|
||||
"""
|
||||
⭐多线程方法
|
||||
@ -15,6 +21,9 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
|
||||
watch_dog_patience = 5
|
||||
response = ""
|
||||
|
||||
if validate_key() is False:
|
||||
raise RuntimeError('请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET')
|
||||
|
||||
from .com_sparkapi import SparkRequestInstance
|
||||
sri = SparkRequestInstance()
|
||||
for response in sri.generate(inputs, llm_kwargs, history, sys_prompt):
|
||||
@ -32,6 +41,10 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
||||
chatbot.append((inputs, ""))
|
||||
yield from update_ui(chatbot=chatbot, history=history)
|
||||
|
||||
if validate_key() is False:
|
||||
yield from update_ui_lastest_msg(lastmsg="[Local Message]: 请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET", chatbot=chatbot, history=history, delay=0)
|
||||
return
|
||||
|
||||
if additional_fn is not None:
|
||||
from core_functional import handle_core_functionality
|
||||
inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
|
||||
|
@ -58,7 +58,7 @@ class Ws_Param(object):
|
||||
class SparkRequestInstance():
|
||||
def __init__(self):
|
||||
XFYUN_APPID, XFYUN_API_SECRET, XFYUN_API_KEY = get_conf('XFYUN_APPID', 'XFYUN_API_SECRET', 'XFYUN_API_KEY')
|
||||
|
||||
if XFYUN_APPID == '00000000' or XFYUN_APPID == '': raise RuntimeError('请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET')
|
||||
self.appid = XFYUN_APPID
|
||||
self.api_secret = XFYUN_API_SECRET
|
||||
self.api_key = XFYUN_API_KEY
|
||||
|
@ -20,4 +20,4 @@ arxiv
|
||||
rich
|
||||
pypdf2==2.12.1
|
||||
websocket-client
|
||||
scipdf_parser==0.3
|
||||
scipdf_parser>=0.3
|
||||
|
@ -9,9 +9,10 @@ validate_path() # 返回项目根路径
|
||||
from tests.test_utils import plugin_test
|
||||
|
||||
if __name__ == "__main__":
|
||||
# plugin_test(plugin='crazy_functions.虚空终端->自动终端', main_input='修改api-key为sk-jhoejriotherjep')
|
||||
# plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep')
|
||||
plugin_test(plugin='crazy_functions.批量翻译PDF文档_NOUGAT->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf')
|
||||
|
||||
plugin_test(plugin='crazy_functions.虚空终端->自动终端', main_input='调用插件,对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析')
|
||||
# plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='调用插件,对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析')
|
||||
|
||||
# plugin_test(plugin='crazy_functions.命令行助手->命令行助手', main_input='查看当前的docker容器列表')
|
||||
|
||||
|
@ -1,15 +1,21 @@
|
||||
/* hide remove all button */
|
||||
.remove-all.svelte-aqlk7e.svelte-aqlk7e.svelte-aqlk7e {
|
||||
visibility: hidden;
|
||||
}
|
||||
|
||||
/* hide selector border */
|
||||
#input-plugin-group .wrap.svelte-aqlk7e.svelte-aqlk7e.svelte-aqlk7e {
|
||||
border: 0px;
|
||||
box-shadow: none;
|
||||
}
|
||||
|
||||
/* hide selector label */
|
||||
#input-plugin-group .svelte-1gfkn6j {
|
||||
visibility: hidden;
|
||||
}
|
||||
/* hide remove all button */
|
||||
.remove-all.svelte-aqlk7e.svelte-aqlk7e.svelte-aqlk7e {
|
||||
visibility: hidden;
|
||||
}
|
||||
|
||||
/* hide selector border */
|
||||
#input-plugin-group .wrap.svelte-aqlk7e.svelte-aqlk7e.svelte-aqlk7e {
|
||||
border: 0px;
|
||||
box-shadow: none;
|
||||
}
|
||||
|
||||
/* hide selector label */
|
||||
#input-plugin-group .svelte-1gfkn6j {
|
||||
visibility: hidden;
|
||||
}
|
||||
|
||||
|
||||
/* height of the upload box */
|
||||
.wrap.svelte-xwlu1w {
|
||||
min-height: var(--size-32);
|
||||
}
|
||||
|
94
toolbox.py
94
toolbox.py
@ -24,6 +24,19 @@ pj = os.path.join
|
||||
|
||||
class ChatBotWithCookies(list):
|
||||
def __init__(self, cookie):
|
||||
"""
|
||||
cookies = {
|
||||
'top_p': top_p,
|
||||
'temperature': temperature,
|
||||
'lock_plugin': bool,
|
||||
"files_to_promote": ["file1", "file2"],
|
||||
"most_recent_uploaded": {
|
||||
"path": "uploaded_path",
|
||||
"time": time.time(),
|
||||
"time_str": "timestr",
|
||||
}
|
||||
}
|
||||
"""
|
||||
self._cookies = cookie
|
||||
|
||||
def write_list(self, list):
|
||||
@ -47,6 +60,8 @@ def ArgsGeneralWrapper(f):
|
||||
# 引入一个有cookie的chatbot
|
||||
cookies.update({
|
||||
'top_p':top_p,
|
||||
'api_key': cookies['api_key'],
|
||||
'llm_model': llm_model,
|
||||
'temperature':temperature,
|
||||
})
|
||||
llm_kwargs = {
|
||||
@ -69,7 +84,7 @@ def ArgsGeneralWrapper(f):
|
||||
# 处理个别特殊插件的锁定状态
|
||||
module, fn_name = cookies['lock_plugin'].split('->')
|
||||
f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name)
|
||||
yield from f_hot_reload(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
yield from f_hot_reload(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, request)
|
||||
return decorated
|
||||
|
||||
|
||||
@ -266,8 +281,7 @@ def report_execption(chatbot, history, a, b):
|
||||
向chatbot中添加错误信息
|
||||
"""
|
||||
chatbot.append((a, b))
|
||||
history.append(a)
|
||||
history.append(b)
|
||||
history.extend([a, b])
|
||||
|
||||
|
||||
def text_divide_paragraph(text):
|
||||
@ -290,6 +304,7 @@ def text_divide_paragraph(text):
|
||||
text = "</br>".join(lines)
|
||||
return pre + text + suf
|
||||
|
||||
|
||||
@lru_cache(maxsize=128) # 使用 lru缓存 加快转换速度
|
||||
def markdown_convertion(txt):
|
||||
"""
|
||||
@ -344,19 +359,41 @@ def markdown_convertion(txt):
|
||||
content = content.replace('</script>\n</script>', '</script>')
|
||||
return content
|
||||
|
||||
def no_code(txt):
|
||||
if '```' not in txt:
|
||||
return True
|
||||
else:
|
||||
if '```reference' in txt: return True # newbing
|
||||
else: return False
|
||||
def is_equation(txt):
|
||||
"""
|
||||
判定是否为公式 | 测试1 写出洛伦兹定律,使用tex格式公式 测试2 给出柯西不等式,使用latex格式 测试3 写出麦克斯韦方程组
|
||||
"""
|
||||
if '```' in txt and '```reference' not in txt: return False
|
||||
if '$' not in txt and '\\[' not in txt: return False
|
||||
mathpatterns = {
|
||||
r'(?<!\\|\$)(\$)([^\$]+)(\$)': {'allow_multi_lines': False}, # $...$
|
||||
r'(?<!\\)(\$\$)([^\$]+)(\$\$)': {'allow_multi_lines': True}, # $$...$$
|
||||
r'(?<!\\)(\\\[)(.+?)(\\\])': {'allow_multi_lines': False}, # \[...\]
|
||||
# r'(?<!\\)(\\\()(.+?)(\\\))': {'allow_multi_lines': False}, # \(...\)
|
||||
# r'(?<!\\)(\\begin{([a-z]+?\*?)})(.+?)(\\end{\2})': {'allow_multi_lines': True}, # \begin...\end
|
||||
# r'(?<!\\)(\$`)([^`]+)(`\$)': {'allow_multi_lines': False}, # $`...`$
|
||||
}
|
||||
matches = []
|
||||
for pattern, property in mathpatterns.items():
|
||||
flags = re.ASCII|re.DOTALL if property['allow_multi_lines'] else re.ASCII
|
||||
matches.extend(re.findall(pattern, txt, flags))
|
||||
if len(matches) == 0: return False
|
||||
contain_any_eq = False
|
||||
illegal_pattern = re.compile(r'[^\x00-\x7F]|echo')
|
||||
for match in matches:
|
||||
if len(match) != 3: return False
|
||||
eq_canidate = match[1]
|
||||
if illegal_pattern.search(eq_canidate):
|
||||
return False
|
||||
else:
|
||||
contain_any_eq = True
|
||||
return contain_any_eq
|
||||
|
||||
if ('$' in txt) and no_code(txt): # 有$标识的公式符号,且没有代码段```的标识
|
||||
if is_equation(txt): # 有$标识的公式符号,且没有代码段```的标识
|
||||
# convert everything to html format
|
||||
split = markdown.markdown(text='---')
|
||||
convert_stage_1 = markdown.markdown(text=txt, extensions=['mdx_math', 'fenced_code', 'tables', 'sane_lists'], extension_configs=markdown_extension_configs)
|
||||
convert_stage_1 = markdown.markdown(text=txt, extensions=['sane_lists', 'tables', 'mdx_math', 'fenced_code'], extension_configs=markdown_extension_configs)
|
||||
convert_stage_1 = markdown_bug_hunt(convert_stage_1)
|
||||
# re.DOTALL: Make the '.' special character match any character at all, including a newline; without this flag, '.' will match anything except a newline. Corresponds to the inline flag (?s).
|
||||
# 1. convert to easy-to-copy tex (do not render math)
|
||||
convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL)
|
||||
# 2. convert to rendered equation
|
||||
@ -364,7 +401,7 @@ def markdown_convertion(txt):
|
||||
# cat them together
|
||||
return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf
|
||||
else:
|
||||
return pre + markdown.markdown(txt, extensions=['fenced_code', 'codehilite', 'tables', 'sane_lists']) + suf
|
||||
return pre + markdown.markdown(txt, extensions=['sane_lists', 'tables', 'fenced_code', 'codehilite']) + suf
|
||||
|
||||
|
||||
def close_up_code_segment_during_stream(gpt_reply):
|
||||
@ -479,7 +516,8 @@ def find_recent_files(directory):
|
||||
current_time = time.time()
|
||||
one_minute_ago = current_time - 60
|
||||
recent_files = []
|
||||
|
||||
if not os.path.exists(directory):
|
||||
os.makedirs(directory, exist_ok=True)
|
||||
for filename in os.listdir(directory):
|
||||
file_path = os.path.join(directory, filename)
|
||||
if file_path.endswith('.log'):
|
||||
@ -503,15 +541,15 @@ def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
|
||||
if not os.path.exists(new_path): shutil.copyfile(file, new_path)
|
||||
# 将文件添加到chatbot cookie中,避免多用户干扰
|
||||
if chatbot:
|
||||
if 'file_to_promote' in chatbot._cookies: current = chatbot._cookies['file_to_promote']
|
||||
if 'files_to_promote' in chatbot._cookies: current = chatbot._cookies['files_to_promote']
|
||||
else: current = []
|
||||
chatbot._cookies.update({'file_to_promote': [new_path] + current})
|
||||
chatbot._cookies.update({'files_to_promote': [new_path] + current})
|
||||
|
||||
def disable_auto_promotion(chatbot):
|
||||
chatbot._cookies.update({'file_to_promote': []})
|
||||
chatbot._cookies.update({'files_to_promote': []})
|
||||
return
|
||||
|
||||
def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
|
||||
def on_file_uploaded(files, chatbot, txt, txt2, checkboxes, cookies):
|
||||
"""
|
||||
当文件被上传时的回调函数
|
||||
"""
|
||||
@ -545,15 +583,21 @@ def on_file_uploaded(files, chatbot, txt, txt2, checkboxes):
|
||||
chatbot.append(['我上传了文件,请查收',
|
||||
f'[Local Message] 收到以下文件: \n\n{moved_files_str}' +
|
||||
f'\n\n调用路径参数已自动修正到: \n\n{txt}' +
|
||||
f'\n\n现在您点击任意“红颜色”标识的函数插件时,以上文件将被作为输入参数'+err_msg])
|
||||
return chatbot, txt, txt2
|
||||
f'\n\n现在您点击任意函数插件时,以上文件将被作为输入参数'+err_msg])
|
||||
cookies.update({
|
||||
'most_recent_uploaded': {
|
||||
'path': f'private_upload/{time_tag}',
|
||||
'time': time.time(),
|
||||
'time_str': time_tag
|
||||
}})
|
||||
return chatbot, txt, txt2, cookies
|
||||
|
||||
|
||||
def on_report_generated(cookies, files, chatbot):
|
||||
from toolbox import find_recent_files
|
||||
if 'file_to_promote' in cookies:
|
||||
report_files = cookies['file_to_promote']
|
||||
cookies.pop('file_to_promote')
|
||||
if 'files_to_promote' in cookies:
|
||||
report_files = cookies['files_to_promote']
|
||||
cookies.pop('files_to_promote')
|
||||
else:
|
||||
report_files = find_recent_files('gpt_log')
|
||||
if len(report_files) == 0:
|
||||
@ -1001,7 +1045,7 @@ def get_plugin_default_kwargs():
|
||||
chatbot = ChatBotWithCookies(llm_kwargs)
|
||||
|
||||
# txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port
|
||||
default_plugin_kwargs = {
|
||||
DEFAULT_FN_GROUPS_kwargs = {
|
||||
"main_input": "./README.md",
|
||||
"llm_kwargs": llm_kwargs,
|
||||
"plugin_kwargs": {},
|
||||
@ -1010,7 +1054,7 @@ def get_plugin_default_kwargs():
|
||||
"system_prompt": "You are a good AI.",
|
||||
"web_port": WEB_PORT
|
||||
}
|
||||
return default_plugin_kwargs
|
||||
return DEFAULT_FN_GROUPS_kwargs
|
||||
|
||||
def get_chat_default_kwargs():
|
||||
"""
|
||||
|
4
version
4
version
@ -1,5 +1,5 @@
|
||||
{
|
||||
"version": 3.49,
|
||||
"version": 3.50,
|
||||
"show_feature": true,
|
||||
"new_feature": "支持借助GROBID实现PDF高精度翻译 <-> 接入百度千帆平台和文心一言 <-> 接入阿里通义千问、讯飞星火、上海AI-Lab书生 <-> 优化一键升级 <-> 提高arxiv翻译速度和成功率 <-> 支持自定义APIKEY格式 <-> 临时修复theme的文件丢失问题 <-> 新增实时语音对话插件(自动断句,脱手对话) <-> 支持加载自定义的ChatGLM2微调模型 <-> 动态ChatBot窗口高度 <-> 修复Azure接口的BUG <-> 完善多语言模块"
|
||||
"new_feature": "支持插件分类! <-> 支持用户使用自然语言调度各个插件(虚空终端) ! <-> 改进UI,设计新主题 <-> 支持借助GROBID实现PDF高精度翻译 <-> 接入百度千帆平台和文心一言 <-> 接入阿里通义千问、讯飞星火、上海AI-Lab书生 <-> 优化一键升级 <-> 提高arxiv翻译速度和成功率"
|
||||
}
|
||||
|
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Block a user