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148 Commits

Author SHA1 Message Date
binary-husky
32ddcd067a Merge branch 'master' of github.com:binary-husky/chatgpt_academic 2023-10-16 00:05:53 +08:00
binary-husky
98ef658307 修复warmup模块的延迟问题 2023-10-16 00:05:31 +08:00
binary-husky
a4de91d000 修改缩进 2023-10-15 22:53:57 +08:00
binary-husky
1bb437a5d0 微调提示 2023-10-15 21:17:00 +08:00
binary-husky
4421219c2b Merge branch 'frontier' 2023-10-15 20:56:49 +08:00
binary-husky
ea28db855d 完善自定义菜单 2023-10-15 20:54:16 +08:00
binary-husky
5aea7b3d09 多线程运行微调 2023-10-15 19:13:25 +08:00
binary-husky
5274117cf1 缺失摘要时,插入伪摘要 2023-10-14 23:48:37 +08:00
binary-husky
673faf8cef Grobid负载均衡 2023-10-14 19:59:35 +08:00
binary-husky
130ae31d55 Merge pull request #1168 from Menghuan1918/master
fix bug  #1167 学术小助手在proxies返回空时会首先尝试直接连接
2023-10-13 17:02:01 +08:00
Menghuan1918
c3abc46d4d 在proxies返回空时会首先尝试直接连接 2023-10-13 15:23:06 +08:00
binary-husky
4df75d49ad 兼容一些第三方代理 2023-10-12 23:42:45 +08:00
binary-husky
9ea0fe4de2 Update GithubAction+NoLocal+Latex 2023-10-12 21:23:15 +08:00
binary-husky
8698c5a80f Merge pull request #1159 from Skyzayre/patch-1
Update Dockerfile
2023-10-11 17:18:28 +08:00
binary-husky
383f7f4f77 add webrtcvad dependency 2023-10-11 15:51:34 +08:00
binary-husky
34d784df79 12 2023-10-11 15:48:25 +08:00
binary-husky
662bebfc02 SSL 2023-10-11 15:34:06 +08:00
binary-husky
0c3b00fc6b cookie space 2023-10-11 12:33:50 +08:00
binary-husky
b6e370e8c9 ymp 2023-10-11 11:30:34 +08:00
binary-husky
71ea8e584a 自定义基础功能区按钮 2023-10-11 11:21:41 +08:00
Skyzayre
a5491b9199 Update Dockerfile
gradio已经更新到3.32.6,但是Dockerfile中仍然是3.32.2
2023-10-11 00:26:16 +08:00
binary-husky
6f383c1dc8 支持自定义基础功能区 2023-10-11 00:14:56 +08:00
binary-husky
500a0cbd16 大幅优化语音助手 2023-10-09 01:18:05 +08:00
binary-husky
1ef6730369 Update README.md 2023-10-08 23:14:07 +08:00
binary-husky
491174095a 更新docker-compose说明 2023-10-07 11:59:06 +08:00
binary-husky
02c270410c 减小Latex容器体积 2023-10-06 11:44:10 +08:00
binary-husky
89eec21f27 随机选择, 绕过openai访问频率限制 2023-10-06 10:50:41 +08:00
binary-husky
49cea97822 启动主题自动转换 2023-10-06 10:36:30 +08:00
binary-husky
6310b65d70 重新编译Gradio优化使用体验 2023-10-06 10:32:03 +08:00
binary-husky
93c76e1809 更新内置gradio版本 2023-10-06 09:54:07 +08:00
binary-husky
f64cf7a3d1 update translation matrix 2023-10-02 14:24:01 +08:00
binary-husky
fdffbee1b0 Update toolbox.py 2023-09-30 09:56:30 +08:00
binary-husky
87ccd1a89a Update crazy_functional.py 2023-09-27 18:35:06 +08:00
binary-husky
87b9734986 修复'copiedIcon'重复定义BUG 2023-09-27 16:35:58 +08:00
binary-husky
d2d5665c37 允许模块预热时使用Proxy 2023-09-27 15:53:45 +08:00
binary-husky
0844b6e9cf GROBID服务代理访问支持 2023-09-27 15:40:55 +08:00
binary-husky
9cb05e5724 修改布局 2023-09-27 15:20:28 +08:00
binary-husky
80b209fa0c Merge branch 'frontier' 2023-09-27 15:19:07 +08:00
binary-husky
8d4cb05738 Matlab项目解析插件的Shortcut 2023-09-26 10:16:38 +08:00
binary-husky
31f4069563 改善润色和校读Prompt 2023-09-25 17:46:28 +08:00
binary-husky
8ba6fc062e Merge branch 'frontier' of github.com:binary-husky/chatgpt_academic into frontier 2023-09-23 23:59:30 +08:00
binary-husky
c0c2d14e3d better scrollbar 2023-09-23 23:58:32 +08:00
binary-husky
f0a5c49a9c Merge branch 'frontier' of github.com:binary-husky/chatgpt_academic into frontier 2023-09-23 23:47:42 +08:00
binary-husky
9333570ab7 减小重置等基础按钮的最小大小 2023-09-23 23:47:25 +08:00
binary-husky
d6eaaad962 禁止gradio显示误导性的share=True 2023-09-23 23:23:23 +08:00
binary-husky
e24f077b68 显式增加azure-gpt-4选项 2023-09-23 23:06:58 +08:00
binary-husky
dc5bb9741a 版本更新 2023-09-23 22:45:07 +08:00
binary-husky
b383b45191 version 3.54 beta 2023-09-23 22:44:18 +08:00
binary-husky
2d8f37baba 细分代理场景 2023-09-23 22:43:15 +08:00
binary-husky
409927ef8e 统一 transformers 版本 2023-09-23 22:26:28 +08:00
binary-husky
5b231e0170 添加整体复制按钮 2023-09-23 22:11:29 +08:00
binary-husky
87f629bb37 添加gpt-4-32k 2023-09-23 20:24:13 +08:00
binary-husky
3672c97a06 动态代码解释器 2023-09-23 01:51:05 +08:00
binary-husky
b6ee3e9807 Merge pull request #1121 from binary-husky/frontier
arxiv翻译插件添加禁用缓存选项
2023-09-21 09:33:19 +08:00
binary-husky
d56bc280e9 添加禁用缓存选项 2023-09-20 22:04:15 +08:00
qingxu fu
d5fd00c15d 微调Dockerfile 2023-09-20 10:02:10 +08:00
binary-husky
5e647ff149 Merge branch 'master' into frontier 2023-09-19 17:21:02 +08:00
binary-husky
868faf00cc 修正docker compose 2023-09-19 17:10:57 +08:00
binary-husky
a0286c39b9 更新README 2023-09-19 17:08:20 +08:00
binary-husky
9cced321f1 修改README 2023-09-19 16:55:39 +08:00
binary-husky
3073935e24 修改readme 推送version 3.53 2023-09-19 16:49:33 +08:00
binary-husky
ef6631b280 TOKEN_LIMIT_PER_FRAGMENT修改为1024 2023-09-19 16:31:36 +08:00
binary-husky
0801e4d881 Merge pull request #1111 from kaixindelele/only_chinese_pdf
提升PDF翻译插件的效果
2023-09-19 15:56:04 +08:00
qingxu fu
ae08cfbcae 修复小Bug 2023-09-19 15:55:27 +08:00
qingxu fu
1c0d5361ea 调整状态栏的最小高度 2023-09-19 15:52:42 +08:00
qingxu fu
278464bfb7 合并重复的函数 2023-09-18 23:03:23 +08:00
qingxu fu
2a6996f5d0 修复Azure的ENDPOINT格式兼容性 2023-09-18 21:19:02 +08:00
qingxu fu
84b11016c6 在nougat处理结束后,同时输出mmd文件 2023-09-18 15:21:30 +08:00
qingxu fu
7e74d3d699 调整按钮位置 2023-09-18 15:19:21 +08:00
qingxu fu
2cad8e2694 支持动态切换主题 2023-09-17 00:15:28 +08:00
qingxu fu
e765ec1223 dynamic theme 2023-09-17 00:02:49 +08:00
kaixindelele
471a369bb8 论文翻译只输出中文 2023-09-16 22:09:44 +08:00
binary-husky
760ff1840c 修复一个循环的Bug 2023-09-15 17:08:23 +08:00
binary-husky
9905122fc2 修复Tex文件匹配BUG 2023-09-15 12:55:41 +08:00
binary-husky
abea0d07ac 修复logging的Bug 2023-09-15 11:00:30 +08:00
binary-husky
16ff5ddcdc 版本3.52 2023-09-14 23:07:12 +08:00
binary-husky
1c4cb340ca 修复滞留文档的提示Bug 2023-09-14 22:45:45 +08:00
binary-husky
5ba8ea27d1 用logging取代print 2023-09-14 22:33:07 +08:00
binary-husky
567c6530d8 增加NOUGAT消息提示和错误操作提示 2023-09-14 21:38:47 +08:00
binary-husky
a3f36668a8 修复latex识别主文件错误的问题 2023-09-14 17:51:41 +08:00
binary-husky
a1cc2f733c 修复nougat线程锁释放Bug 2023-09-14 15:26:03 +08:00
binary-husky
0937f37388 Predict按钮参数修正 2023-09-14 11:02:40 +08:00
binary-husky
74f35e3401 针对虚空终端个别情况下不输出文件的问题进行提示 2023-09-14 01:51:55 +08:00
binary-husky
ab7999c71a 修正本项目源码范围 2023-09-14 01:00:38 +08:00
binary-husky
544771db9a 隐藏历史对话绝对路径 2023-09-14 00:53:15 +08:00
binary-husky
ec9d030457 把上传文件路径和日志路径修改为统一可配置的变量 2023-09-14 00:51:25 +08:00
binary-husky
14de282302 给nougat加线程锁 合并冗余代码 2023-09-13 23:21:00 +08:00
binary-husky
fb5467b85b 更新插件系统提示 2023-09-12 19:13:36 +08:00
binary-husky
c4c6465927 解决issues #1097 2023-09-12 18:57:50 +08:00
qingxu fu
99a1cd6f9f 添加pypinyin依赖 2023-09-12 12:20:05 +08:00
qingxu fu
7e73a255f4 修改知识库插件的提示信息 2023-09-12 11:47:34 +08:00
qingxu fu
4b5f13bff2 修复知识库的依赖问题 2023-09-12 11:35:31 +08:00
qingxu fu
d495b73456 支持更多UI皮肤外观,加入暗色亮色切换键 2023-09-11 22:55:32 +08:00
qingxu fu
e699b6b13f Merge branch 'master' of https://github.com/binary-husky/chatgpt_academic into master 2023-09-11 14:49:37 +08:00
qingxu fu
eb150987f0 兼容一个one-api没有done数据包的第三方Bug情形 2023-09-11 14:49:30 +08:00
binary-husky
34784333dc 融合PDF左右比例调整到95% 2023-09-10 17:22:35 +08:00
binary-husky
28d777a96b 修正报错消息 2023-09-10 16:52:35 +08:00
qingxu fu
c45fa88684 update translation matrix 2023-09-09 21:57:24 +08:00
binary-husky
ad9807dd14 更新虚空终端的提示 2023-09-09 20:32:44 +08:00
binary-husky
2a51715075 修复Dockerfile 2023-09-09 20:15:46 +08:00
binary-husky
7c307d8964 修复源代码解析模块与虚空终端的兼容性 2023-09-09 19:33:05 +08:00
binary-husky
baaacc5a7b Update README.md 2023-09-09 19:11:21 +08:00
binary-husky
6faf5947c9 Merge branch 'master' of github.com:binary-husky/chatgpt_academic 2023-09-09 18:30:59 +08:00
binary-husky
571335cbc4 fix docker file 2023-09-09 18:30:43 +08:00
binary-husky
7d5abb6d69 Merge pull request #1077 from jsz14897502/master
更改谷歌学术搜索助手获取摘要的逻辑
2023-09-09 18:24:30 +08:00
binary-husky
a0f592308a Merge branch 'master' into jsz14897502-master 2023-09-09 18:22:29 +08:00
binary-husky
e512d99879 添加一定的延迟,防止触发反爬虫机制 2023-09-09 18:22:22 +08:00
binary-husky
e70b636513 修复数学公式判定的Bug 2023-09-09 17:50:38 +08:00
binary-husky
408b8403fe Merge branch 'master' of github.com:binary-husky/chatgpt_academic 2023-09-08 12:10:22 +08:00
binary-husky
74f8cb3511 update dockerfile 2023-09-08 12:10:16 +08:00
qingxu fu
2202cf3701 remove proxy message 2023-09-08 11:11:53 +08:00
qingxu fu
cce69beee9 update error message 2023-09-08 11:08:02 +08:00
qingxu fu
347124c967 update scipdf_parser dep 2023-09-08 10:43:20 +08:00
qingxu fu
77a6105a9a 修改demo案例 2023-09-08 09:52:29 +08:00
qingxu fu
13c9606af7 修正下载PDF失败时产生的错误提示 2023-09-08 09:47:29 +08:00
binary-husky
bac6810e75 修改操作提示 2023-09-08 09:38:16 +08:00
binary-husky
c176187d24 修复因为函数返回值导致的不准确错误提示 2023-09-07 23:46:54 +08:00
binary-husky
31d5ee6ccc Update README.md 2023-09-07 23:05:54 +08:00
binary-husky
5e0dc9b9ad 修复PDF下载路径时间戳的问题 2023-09-07 18:51:09 +08:00
binary-husky
4c6f3aa427 CodeInterpreter 2023-09-07 17:45:44 +08:00
binary-husky
d7331befc1 add note 2023-09-07 17:42:47 +08:00
binary-husky
63219baa21 修正语音对话时 句子末尾显示异常的问题 2023-09-07 17:04:40 +08:00
binary-husky
97cb9a4adc full capacity docker file 2023-09-07 15:09:38 +08:00
binary-husky
24f41b0a75 new docker file 2023-09-07 00:45:03 +08:00
binary-husky
bfec29e9bc new docker file 2023-09-07 00:43:31 +08:00
binary-husky
dd9e624761 add new dockerfile 2023-09-07 00:40:11 +08:00
binary-husky
7855325ff9 update dockerfiles 2023-09-06 23:33:15 +08:00
binary-husky
2c039ff5c9 add session 2023-09-06 22:19:32 +08:00
binary-husky
9a5ee86434 Merge pull request #1084 from eltociear/patch-2
Update README.md
2023-09-06 21:56:39 +08:00
binary-husky
d6698db257 nougat翻译PDF论文 2023-09-06 15:32:11 +08:00
Ikko Eltociear Ashimine
b2d03bf2a3 Update README.md
arbitary -> arbitrary
2023-09-06 15:30:12 +09:00
binary-husky
2f83b60fb3 添加搜索失败时的提示 2023-09-06 12:36:59 +08:00
binary-husky
d183e34461 添加一个全版本搜索的开关 2023-09-06 11:42:29 +08:00
binary-husky
fb78569335 Merge branch 'master' of https://github.com/jsz14897502/gpt_academic into jsz14897502-master 2023-09-06 10:27:52 +08:00
qingxu fu
12c8cd75ee Merge branch 'master' of https://github.com/binary-husky/chatgpt_academic into master 2023-09-06 10:24:14 +08:00
qingxu fu
0e21e3e2e7 修复没填写讯飞APPID无报错提示的问题 2023-09-06 10:24:11 +08:00
binary-husky
fda1e87278 Update stale.yml 2023-09-06 10:19:21 +08:00
binary-husky
1092031d77 Create stale.yml 2023-09-06 10:15:52 +08:00
binary-husky
f0482d3bae Update docker-compose.yml 2023-09-04 12:39:25 +08:00
binary-husky
b6ac3d0d6c Update README.md 2023-09-04 12:34:55 +08:00
binary-husky
3344ffcb8b Update README.md 2023-09-04 11:41:52 +08:00
binary-husky
82936f71b6 Update README.md 2023-09-04 11:37:47 +08:00
binary-husky
51e809c09e Update README.md 2023-09-04 11:34:46 +08:00
qingxu fu
713df396dc Merge branch 'master' of https://github.com/binary-husky/chatgpt_academic into master 2023-09-03 16:46:30 +08:00
qingxu fu
23a42d93df update translation matrix 2023-09-03 16:46:27 +08:00
binary-husky
0ef06683dc Update README.md 2023-09-03 16:35:03 +08:00
jsz14
03164bcb6f fix:没有获取到所有版本时的处理 2023-09-02 19:58:24 +08:00
jsz14
d052d425af 更改谷歌学术搜索助手获取摘要的逻辑 2023-08-30 19:14:01 +08:00
81 changed files with 3092 additions and 968 deletions

View 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
View 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

View File

@@ -17,7 +17,7 @@ WORKDIR /gpt
# 安装大部分依赖利用Docker缓存加速以后的构建
COPY requirements.txt ./
COPY ./docs/gradio-3.32.2-py3-none-any.whl ./docs/gradio-3.32.2-py3-none-any.whl
COPY ./docs/gradio-3.32.6-py3-none-any.whl ./docs/gradio-3.32.6-py3-none-any.whl
RUN pip3 install -r requirements.txt

View File

@@ -1,6 +1,6 @@
> **Note**
>
> 2023.7.8: Gradio, Pydantic依赖调整已修改 `requirements.txt`。请及时**更新代码**,安装依赖时,请严格选择`requirements.txt`中**指定的版本**
> 2023.10.8: Gradio, Pydantic依赖调整已修改 `requirements.txt`。请及时**更新代码**,安装依赖时,请严格选择`requirements.txt`中**指定的版本**
>
> `pip install -r requirements.txt`
@@ -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/GPTAcademic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/GPTAcademic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>
@@ -100,9 +101,11 @@ cd gpt_academic
2. 配置API_KEY
在`config.py`中配置API KEY等设置[点击查看特殊网络环境设置方法](https://github.com/binary-husky/gpt_academic/issues/1) 。
在`config.py`中配置API KEY等设置[点击查看特殊网络环境设置方法](https://github.com/binary-husky/gpt_academic/issues/1) 。[Wiki页面](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)。
(P.S. 程序运行时会优先检查是否存在名为`config_private.py`的私密配置文件,并用其中的配置覆盖`config.py`的同名配置。因此,如果您能理解我们的配置读取逻辑,我们强烈建议您在`config.py`旁边创建一个名为`config_private.py`的新配置文件,并把`config.py`中的配置转移(复制)到`config_private.py`中(仅复制您修改过的配置条目即可)。`config_private.py`不受git管控可以让您的隐私信息更加安全。P.S.项目同样支持通过`环境变量`配置大多数选项,环境变量的书写格式参考`docker-compose`文件。读取优先级: `环境变量` > `config_private.py` > `config.py`)
「 程序会优先检查是否存在名为`config_private.py`的私密配置文件,并用其中的配置覆盖`config.py`的同名配置。如您能理解该读取逻辑,我们强烈建议您在`config.py`旁边创建一个名为`config_private.py`的新配置文件,并把`config.py`中的配置转移(复制)到`config_private.py`中(仅复制您修改过的配置条目即可)。
「 支持通过`环境变量`配置项目,环境变量的书写格式参考`docker-compose.yml`文件或者我们的[Wiki页面](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)。配置读取优先级: `环境变量` > `config_private.py` > `config.py`。 」
3. 安装依赖
@@ -110,7 +113,7 @@ cd gpt_academic
# 选择I: 如熟悉pythonpython版本3.9以上越新越好备注使用官方pip源或者阿里pip源,临时换源方法python -m pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/
python -m pip install -r requirements.txt
# 选择II: 如不熟悉python使用anaconda步骤也是类似的 (https://www.bilibili.com/video/BV1rc411W7Dr)
# 选择II: 使用Anaconda步骤也是类似的 (https://www.bilibili.com/video/BV1rc411W7Dr)
conda create -n gptac_venv python=3.11 # 创建anaconda环境
conda activate gptac_venv # 激活anaconda环境
python -m pip install -r requirements.txt # 这个步骤和pip安装一样的步骤
@@ -148,23 +151,25 @@ python main.py
### 安装方法II使用Docker
1. 仅ChatGPT推荐大多数人选择等价于docker-compose方案1
0. 部署项目的全部能力这个是包含cuda和latex的大型镜像。如果您网速慢、硬盘小或没有显卡则不推荐使用这个建议使用方案1需要熟悉[Nvidia Docker](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#installing-on-ubuntu-and-debian)运行时
[![fullcapacity](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-all-capacity.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml)
``` sh
# 修改docker-compose.yml保留方案0并删除其他方案。修改docker-compose.yml中方案0的配置参考其中注释即可
docker-compose up
```
1. 仅ChatGPT+文心一言+spark等在线模型推荐大多数人选择
[![basic](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-without-local-llms.yml)
[![basiclatex](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-latex.yml)
[![basicaudio](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-audio-assistant.yml)
``` sh
git clone --depth=1 https://github.com/binary-husky/gpt_academic.git # 下载项目
cd gpt_academic # 进入路径
nano config.py # 用任意文本编辑器编辑config.py, 配置 “Proxy” “API_KEY” 以及 “WEB_PORT” (例如50923) 等
docker build -t gpt-academic . # 安装
#(最后一步-Linux操作系统用`--net=host`更方便快捷
docker run --rm -it --net=host gpt-academic
#(最后一步-MacOS/Windows操作系统只能用-p选项将容器上的端口(例如50923)暴露给主机上的端口
docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic
# 修改docker-compose.yml保留方案1并删除其他方案。修改docker-compose.yml中方案1的配置参考其中注释即可
docker-compose up
```
P.S. 如果需要依赖Latex的插件功能请见Wiki。另外您也可以直接使用docker-compose获取Latex功能修改docker-compose.yml保留方案4并删除其他方案
P.S. 如果需要依赖Latex的插件功能请见Wiki。另外您也可以直接使用方案4或者方案0获取Latex功能。
2. ChatGPT + ChatGLM2 + MOSS + LLAMA2 + 通义千问(需要熟悉[Nvidia Docker](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#installing-on-ubuntu-and-debian)运行时)
[![chatglm](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-chatglm.yml/badge.svg?branch=master)](https://github.com/binary-husky/gpt_academic/actions/workflows/build-with-chatglm.yml)
@@ -249,10 +254,13 @@ 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://openreview.net/pdf?id=rJl0r3R9KX ”
- 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 +307,12 @@ 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 3.60todo: 优化虚空终端引入code interpreter和更多插件
- version 3.55: 重构前端界面,引入悬浮窗口与菜单栏
- version 3.54: 新增动态代码解释器Code Interpreter待完善
- version 3.53: 支持动态选择不同界面主题,提高稳定性&解决多用户冲突问题
- 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
@@ -321,7 +333,7 @@ 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
- version 2.0: 引入模块化函数插件
- version 1.0: 基础功能
gpt_academic开发者QQ群-2610599535
GPT Academic开发者QQ群`610599535`
- 已知问题
- 某些浏览器翻译插件干扰此软件前端的运行

View File

@@ -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}"
@@ -155,11 +155,13 @@ def auto_update(raise_error=False):
def warm_up_modules():
print('正在执行一些模块的预热...')
from toolbox import ProxyNetworkActivate
from request_llm.bridge_all import model_info
enc = model_info["gpt-3.5-turbo"]['tokenizer']
enc.encode("模块预热", disallowed_special=())
enc = model_info["gpt-4"]['tokenizer']
enc.encode("模块预热", disallowed_special=())
with ProxyNetworkActivate("Warmup_Modules"):
enc = model_info["gpt-3.5-turbo"]['tokenizer']
enc.encode("模块预热", disallowed_special=())
enc = model_info["gpt-4"]['tokenizer']
enc.encode("模块预热", disallowed_special=())
if __name__ == '__main__':
import os

View File

@@ -43,8 +43,10 @@ API_URL_REDIRECT = {}
DEFAULT_WORKER_NUM = 3
# 色彩主题可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
# 色彩主题, 可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
# 更多主题, 请查阅Gradio主题商店: https://huggingface.co/spaces/gradio/theme-gallery 可选 ["Gstaff/Xkcd", "NoCrypt/Miku", ...]
THEME = "Default"
AVAIL_THEMES = ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast", "Gstaff/Xkcd", "NoCrypt/Miku"]
# 对话窗的高度 仅在LAYOUT="TOP-DOWN"时生效)
@@ -57,7 +59,10 @@ CODE_HIGHLIGHT = True
# 窗口布局
LAYOUT = "LEFT-RIGHT" # "LEFT-RIGHT"(左右布局) # "TOP-DOWN"(上下布局)
DARK_MODE = True # 暗色模式 / 亮色模式
# 暗色模式 / 亮色模式
DARK_MODE = True
# 发送请求到OpenAI后等待多久判定为超时
@@ -73,14 +78,14 @@ MAX_RETRY = 2
# 插件分类默认选项
DEFAULT_FN_GROUPS = ['对话', '编程', '学术']
DEFAULT_FN_GROUPS = ['对话', '编程', '学术', '智能体']
# 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",
"gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
# P.S. 其他可用的模型还包括 ["qianfan", "llama2", "qwen", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613",
"gpt-4", "gpt-4-32k", "azure-gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
# P.S. 其他可用的模型还包括 ["qianfan", "llama2", "qwen", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "gpt-3.5-random"
# "spark", "sparkv2", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
@@ -120,6 +125,11 @@ AUTHENTICATION = []
CUSTOM_PATH = "/"
# HTTPS 秘钥和证书(不需要修改)
SSL_KEYFILE = ""
SSL_CERTFILE = ""
# 极少数情况下openai的官方KEY需要伴随组织编码格式如org-xxxxxxxxxxxxxxxxxxxxxxxx使用
API_ORG = ""
@@ -135,7 +145,7 @@ AZURE_API_KEY = "填入azure openai api的密钥" # 建议直接在API_KEY处
AZURE_ENGINE = "填入你亲手写的部署名" # 读 docs\use_azure.md
# 使用Newbing
# 使用Newbing (不推荐使用,未来将删除)
NEWBING_STYLE = "creative" # ["creative", "balanced", "precise"]
NEWBING_COOKIES = """
put your new bing cookies here
@@ -172,7 +182,8 @@ HUGGINGFACE_ACCESS_TOKEN = "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"
# 获取方法复制以下空间https://huggingface.co/spaces/qingxu98/grobid设为public然后GROBID_URL = "https://(你的hf用户名如qingxu98)-(你的填写的空间名如grobid).hf.space"
GROBID_URLS = [
"https://qingxu98-grobid.hf.space","https://qingxu98-grobid2.hf.space","https://qingxu98-grobid3.hf.space",
"https://shaocongma-grobid.hf.space","https://FBR123-grobid.hf.space", "https://yeku-grobid.hf.space",
"https://qingxu98-grobid4.hf.space","https://qingxu98-grobid5.hf.space", "https://qingxu98-grobid6.hf.space",
"https://qingxu98-grobid7.hf.space", "https://qingxu98-grobid8.hf.space",
]
@@ -180,6 +191,21 @@ GROBID_URLS = [
ALLOW_RESET_CONFIG = False
# 临时的上传文件夹位置,请勿修改
PATH_PRIVATE_UPLOAD = "private_upload"
# 日志文件夹的位置,请勿修改
PATH_LOGGING = "gpt_log"
# 除了连接OpenAI之外还有哪些场合允许使用代理请勿修改
WHEN_TO_USE_PROXY = ["Download_LLM", "Download_Gradio_Theme", "Connect_Grobid", "Warmup_Modules"]
# 自定义按钮的最大数量限制
NUM_CUSTOM_BASIC_BTN = 4
"""
在线大模型配置关联关系示意图

View File

@@ -11,7 +11,8 @@ def get_core_functions():
# 前缀,会被加在你的输入之前。例如,用来描述你的要求,例如翻译、解释代码、润色等等
"Prefix": r"Below is a paragraph from an academic paper. Polish the writing to meet the academic style, " +
r"improve the spelling, grammar, clarity, concision and overall readability. When necessary, rewrite the whole sentence. " +
r"Furthermore, list all modification and explain the reasons to do so in markdown table." + "\n\n",
r"Firstly, you should provide the polished paragraph. "
r"Secondly, you should list all your modification and explain the reasons to do so in markdown table." + "\n\n",
# 后缀,会被加在你的输入之后。例如,配合前缀可以把你的输入内容用引号圈起来
"Suffix": r"",
# 按钮颜色 (默认 secondary)
@@ -27,17 +28,18 @@ def get_core_functions():
"Suffix": r"",
},
"查找语法错误": {
"Prefix": r"Can you help me ensure that the grammar and the spelling is correct? " +
r"Do not try to polish the text, if no mistake is found, tell me that this paragraph is good." +
r"If you find grammar or spelling mistakes, please list mistakes you find in a two-column markdown table, " +
r"put the original text the first column, " +
r"put the corrected text in the second column and highlight the key words you fixed.""\n"
"Prefix": r"Help me ensure that the grammar and the spelling is correct. "
r"Do not try to polish the text, if no mistake is found, tell me that this paragraph is good. "
r"If you find grammar or spelling mistakes, please list mistakes you find in a two-column markdown table, "
r"put the original text the first column, "
r"put the corrected text in the second column and highlight the key words you fixed. "
r"Finally, please provide the proofreaded text.""\n\n"
r"Example:""\n"
r"Paragraph: How is you? Do you knows what is it?""\n"
r"| Original sentence | Corrected sentence |""\n"
r"| :--- | :--- |""\n"
r"| How **is** you? | How **are** you? |""\n"
r"| Do you **knows** what **is** **it**? | Do you **know** what **it** **is** ? |""\n"
r"| Do you **knows** what **is** **it**? | Do you **know** what **it** **is** ? |""\n\n"
r"Below is a paragraph from an academic paper. "
r"You need to report all grammar and spelling mistakes as the example before."
+ "\n\n",
@@ -89,8 +91,15 @@ def handle_core_functionality(additional_fn, inputs, history, chatbot):
import core_functional
importlib.reload(core_functional) # 热更新prompt
core_functional = core_functional.get_core_functions()
if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs) # 获取预处理函数(如果有的话)
inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
if core_functional[additional_fn].get("AutoClearHistory", False):
history = []
return inputs, history
addition = chatbot._cookies['customize_fn_overwrite']
if additional_fn in addition:
# 自定义功能
inputs = addition[additional_fn]["Prefix"] + inputs + addition[additional_fn]["Suffix"]
return inputs, history
else:
# 预制功能
if "PreProcess" in core_functional[additional_fn]: inputs = core_functional[additional_fn]["PreProcess"](inputs) # 获取预处理函数(如果有的话)
inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
if core_functional[additional_fn].get("AutoClearHistory", False):
history = []
return inputs, history

View File

@@ -6,6 +6,7 @@ def get_crazy_functions():
from crazy_functions.生成函数注释 import 批量生成函数注释
from crazy_functions.解析项目源代码 import 解析项目本身
from crazy_functions.解析项目源代码 import 解析一个Python项目
from crazy_functions.解析项目源代码 import 解析一个Matlab项目
from crazy_functions.解析项目源代码 import 解析一个C项目的头文件
from crazy_functions.解析项目源代码 import 解析一个C项目
from crazy_functions.解析项目源代码 import 解析一个Golang项目
@@ -13,7 +14,6 @@ def get_crazy_functions():
from crazy_functions.解析项目源代码 import 解析一个Java项目
from crazy_functions.解析项目源代码 import 解析一个前端项目
from crazy_functions.高级功能函数模板 import 高阶功能模板函数
from crazy_functions.代码重写为全英文_多线程 import 全项目切换英文
from crazy_functions.Latex全文润色 import Latex英文润色
from crazy_functions.询问多个大语言模型 import 同时问询
from crazy_functions.解析项目源代码 import 解析一个Lua项目
@@ -39,7 +39,7 @@ def get_crazy_functions():
function_plugins = {
"虚空终端": {
"Group": "对话|编程|学术",
"Group": "对话|编程|学术|智能体",
"Color": "stop",
"AsButton": True,
"Function": HotReload(虚空终端)
@@ -78,6 +78,13 @@ def get_crazy_functions():
"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Matlab项目": {
"Group": "编程",
"Color": "stop",
"AsButton": False,
"Info": "解析一个Matlab项目的所有源文件(.m) | 输入参数为路径",
"Function": HotReload(解析一个Matlab项目)
},
"解析整个C++项目头文件": {
"Group": "编程",
"Color": "stop",
@@ -183,10 +190,10 @@ def get_crazy_functions():
"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": {
"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",
"Info": "查看历史上的今天事件 (这是一个面向开发者的插件Demo) | 不需要输入参数",
"Function": HotReload(高阶功能模板函数)
},
"精准翻译PDF论文": {
@@ -244,20 +251,25 @@ def get_crazy_functions():
"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": "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)
},
# 已经被新插件取代
# "Latex项目全文中译英输入路径或上传压缩包": {
# "Group": "学术",
# "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)
# },
# 已经被新插件取代
# "Latex项目全文英译中(输入路径或上传压缩包": {
# "Group": "学术",
# "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",
@@ -385,7 +397,7 @@ def get_crazy_functions():
try:
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)": {
"Markdown翻译指定翻译成何种语言)": {
"Group": "编程",
"Color": "stop",
"AsButton": False,
@@ -400,12 +412,12 @@ def get_crazy_functions():
try:
from crazy_functions.Langchain知识库 import 知识库问答
function_plugins.update({
"构建知识库(先上传文件素材)": {
"构建知识库(先上传文件素材,再运行此插件": {
"Group": "对话",
"Color": "stop",
"AsButton": False,
"AdvancedArgs": True,
"ArgsReminder": "待注入的知识库名称id, 默认为default",
"ArgsReminder": "此处待注入的知识库名称id, 默认为default。文件进入知识库后可长期保存。可以通过再次调用本插件的方式,向知识库追加更多文档。",
"Function": HotReload(知识库问答)
}
})
@@ -415,12 +427,12 @@ def get_crazy_functions():
try:
from crazy_functions.Langchain知识库 import 读取知识库作答
function_plugins.update({
"知识库问答": {
"知识库问答(构建知识库后,再运行此插件)": {
"Group": "对话",
"Color": "stop",
"AsButton": False,
"AdvancedArgs": True,
"ArgsReminder": "待提取的知识库名称id, 默认为default, 您需要首先调用构建知识库",
"ArgsReminder": "待提取的知识库名称id, 默认为default, 您需要构建知识库后再运行此插件。",
"Function": HotReload(读取知识库作答)
}
})
@@ -430,7 +442,7 @@ def get_crazy_functions():
try:
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": {
"交互功能模板Demo函数查找wallhaven.cc的壁纸": {
"Group": "对话",
"Color": "stop",
"AsButton": False,
@@ -490,17 +502,43 @@ def get_crazy_functions():
if ENABLE_AUDIO:
from crazy_functions.语音助手 import 语音助手
function_plugins.update({
"实时音频采集": {
"实时语音对话": {
"Group": "对话",
"Color": "stop",
"AsButton": True,
"Info": "开始语言对话 | 没有输入参数",
"Info": "这是一个时刻聆听着的语音对话助手 | 没有输入参数",
"Function": HotReload(语音助手)
}
})
except:
print('Load function plugin failed')
try:
from crazy_functions.批量翻译PDF文档_NOUGAT import 批量翻译PDF文档
function_plugins.update({
"精准翻译PDF文档NOUGAT": {
"Group": "学术",
"Color": "stop",
"AsButton": False,
"Function": HotReload(批量翻译PDF文档)
}
})
except:
print('Load function plugin failed')
try:
from crazy_functions.函数动态生成 import 函数动态生成
function_plugins.update({
"动态代码解释器CodeInterpreter": {
"Group": "智能体",
"Color": "stop",
"AsButton": False,
"Function": HotReload(函数动态生成)
}
})
except:
print('Load function plugin failed')
# try:
# from crazy_functions.chatglm微调工具 import 微调数据集生成

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@@ -0,0 +1,232 @@
from collections.abc import Callable, Iterable, Mapping
from typing import Any
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc
from toolbox import promote_file_to_downloadzone, get_log_folder
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'{get_log_folder()}/{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"{get_log_folder().replace('/', '.')}.{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 is_the_upload_folder(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"{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
"""

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@@ -1,4 +1,4 @@
from toolbox import CatchException, update_ui, ProxyNetworkActivate
from toolbox import CatchException, update_ui, ProxyNetworkActivate, update_ui_lastest_msg
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_files_from_everything
@@ -15,7 +15,12 @@ def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
web_port 当前软件运行的端口号
"""
history = [] # 清空历史,以免输入溢出
chatbot.append(("这是什么功能?", "[Local Message] 从一批文件(txt, md, tex)中读取数据构建知识库, 然后进行问答。"))
# < --------------------读取参数--------------- >
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
kai_id = plugin_kwargs.get("advanced_arg", 'default')
chatbot.append((f"向`{kai_id}`知识库中添加文件。", "[Local Message] 从一批文件(txt, md, tex)中读取数据构建知识库, 然后进行问答。"))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# resolve deps
@@ -24,17 +29,12 @@ def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
from .crazy_utils import knowledge_archive_interface
except Exception as e:
chatbot.append(
["依赖不足",
"导入依赖失败。正在尝试自动安装,请查看终端的输出或耐心等待..."]
)
chatbot.append(["依赖不足", "导入依赖失败。正在尝试自动安装,请查看终端的输出或耐心等待..."])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
from .crazy_utils import try_install_deps
try_install_deps(['zh_langchain==0.2.1', 'pypinyin'])
# < --------------------读取参数--------------- >
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
kai_id = plugin_kwargs.get("advanced_arg", 'default')
try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
yield from update_ui_lastest_msg("安装完成,您可以再次重试。", chatbot, history)
return
# < --------------------读取文件--------------- >
file_manifest = []
@@ -53,14 +53,14 @@ def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
print('Checking Text2vec ...')
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
with ProxyNetworkActivate(): # 临时地激活代理网络
with ProxyNetworkActivate('Download_LLM'): # 临时地激活代理网络
HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
# < -------------------构建知识库--------------- >
chatbot.append(['<br/>'.join(file_manifest), "正在构建知识库..."])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
print('Establishing knowledge archive ...')
with ProxyNetworkActivate(): # 临时地激活代理网络
with ProxyNetworkActivate('Download_LLM'): # 临时地激活代理网络
kai = knowledge_archive_interface()
kai.feed_archive(file_manifest=file_manifest, id=kai_id)
kai_files = kai.get_loaded_file()
@@ -84,19 +84,18 @@ def 读取知识库作答(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
chatbot.append(["依赖不足", "导入依赖失败。正在尝试自动安装,请查看终端的输出或耐心等待..."])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
from .crazy_utils import try_install_deps
try_install_deps(['zh_langchain==0.2.1'])
try_install_deps(['zh_langchain==0.2.1', 'pypinyin'], reload_m=['pypinyin', 'zh_langchain'])
yield from update_ui_lastest_msg("安装完成,您可以再次重试。", chatbot, history)
return
# < ------------------- --------------- >
kai = knowledge_archive_interface()
if 'langchain_plugin_embedding' in chatbot._cookies:
resp, prompt = kai.answer_with_archive_by_id(txt, chatbot._cookies['langchain_plugin_embedding'])
else:
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
kai_id = plugin_kwargs.get("advanced_arg", 'default')
resp, prompt = kai.answer_with_archive_by_id(txt, kai_id)
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
kai_id = plugin_kwargs.get("advanced_arg", 'default')
resp, prompt = kai.answer_with_archive_by_id(txt, kai_id)
chatbot.append((txt, '[Local Message] ' + prompt))
chatbot.append((txt, f'[知识库 {kai_id}] ' + prompt))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间我们先及时地做一次界面更新
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=prompt, inputs_show_user=txt,

View File

@@ -1,5 +1,5 @@
from toolbox import update_ui, trimmed_format_exc
from toolbox import CatchException, report_execption, write_results_to_file, zip_folder
from toolbox import update_ui, trimmed_format_exc, promote_file_to_downloadzone, get_log_folder
from toolbox import CatchException, report_execption, write_history_to_file, zip_folder
class PaperFileGroup():
@@ -51,7 +51,7 @@ class PaperFileGroup():
import os, time
folder = os.path.dirname(self.file_paths[0])
t = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
zip_folder(folder, './gpt_log/', f'{t}-polished.zip')
zip_folder(folder, get_log_folder(), f'{t}-polished.zip')
def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='en', mode='polish'):
@@ -126,7 +126,9 @@ def 多文件润色(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
# <-------- 整理结果,退出 ---------->
create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md"
res = write_results_to_file(gpt_response_collection, file_name=create_report_file_name)
res = write_history_to_file(gpt_response_collection, file_basename=create_report_file_name)
promote_file_to_downloadzone(res, chatbot=chatbot)
history = gpt_response_collection
chatbot.append((f"{fp}完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -137,7 +139,7 @@ def Latex英文润色(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
"对整个Latex项目进行润色。函数插件贡献者: Binary-Husky"])
"对整个Latex项目进行润色。函数插件贡献者: Binary-Husky注意此插件不调用Latex如果有Latex环境请使用“Latex英文纠错+高亮”插件)"])
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

View File

@@ -1,5 +1,5 @@
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import update_ui, promote_file_to_downloadzone
from toolbox import CatchException, report_execption, write_history_to_file
fast_debug = False
class PaperFileGroup():
@@ -95,7 +95,8 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
# <-------- 整理结果,退出 ---------->
create_report_file_name = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + f"-chatgpt.polish.md"
res = write_results_to_file(gpt_response_collection, file_name=create_report_file_name)
res = write_history_to_file(gpt_response_collection, create_report_file_name)
promote_file_to_downloadzone(res, chatbot=chatbot)
history = gpt_response_collection
chatbot.append((f"{fp}完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

View File

@@ -1,4 +1,4 @@
from toolbox import update_ui, trimmed_format_exc, get_conf, objdump, objload, promote_file_to_downloadzone
from toolbox import update_ui, trimmed_format_exc, get_conf, get_log_folder, promote_file_to_downloadzone
from toolbox import CatchException, report_execption, update_ui_lastest_msg, zip_result, gen_time_str
from functools import partial
import glob, os, requests, time
@@ -65,7 +65,7 @@ def move_project(project_folder, arxiv_id=None):
if arxiv_id is not None:
new_workfolder = pj(ARXIV_CACHE_DIR, arxiv_id, 'workfolder')
else:
new_workfolder = f'gpt_log/{gen_time_str()}'
new_workfolder = f'{get_log_folder()}/{gen_time_str()}'
try:
shutil.rmtree(new_workfolder)
except:
@@ -79,7 +79,7 @@ def move_project(project_folder, arxiv_id=None):
shutil.copytree(src=project_folder, dst=new_workfolder)
return new_workfolder
def arxiv_download(chatbot, history, txt):
def arxiv_download(chatbot, history, txt, allow_cache=True):
def check_cached_translation_pdf(arxiv_id):
translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'translation')
if not os.path.exists(translation_dir):
@@ -109,14 +109,14 @@ 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 ------------->
arxiv_id = url_.split('/abs/')[-1]
if 'v' in arxiv_id: arxiv_id = arxiv_id[:10]
cached_translation_pdf = check_cached_translation_pdf(arxiv_id)
if cached_translation_pdf: return cached_translation_pdf, arxiv_id
if cached_translation_pdf and allow_cache: return cached_translation_pdf, arxiv_id
url_tar = url_.replace('/abs/', '/e-print/')
translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'e-print')
@@ -228,6 +228,9 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
# <-------------- more requirements ------------->
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
more_req = plugin_kwargs.get("advanced_arg", "")
no_cache = more_req.startswith("--no-cache")
if no_cache: more_req.lstrip("--no-cache")
allow_cache = not no_cache
_switch_prompt_ = partial(switch_prompt, more_requirement=more_req)
# <-------------- check deps ------------->
@@ -244,7 +247,7 @@ def Latex翻译中文并重新编译PDF(txt, llm_kwargs, plugin_kwargs, chatbot,
# <-------------- clear history and read input ------------->
history = []
txt, arxiv_id = yield from arxiv_download(chatbot, history, txt)
txt, arxiv_id = yield from arxiv_download(chatbot, history, txt, allow_cache)
if txt.endswith('.pdf'):
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"发现已经存在翻译好的PDF文档")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -255,7 +258,7 @@ 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

View File

@@ -1,5 +1,7 @@
from toolbox import update_ui, get_conf, trimmed_format_exc
from toolbox import update_ui, get_conf, trimmed_format_exc, get_log_folder
import threading
import os
import logging
def input_clipping(inputs, history, max_token_limit):
import numpy as np
@@ -67,12 +69,15 @@ def request_gpt_model_in_new_thread_with_ui_alive(
yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
executor = ThreadPoolExecutor(max_workers=16)
mutable = ["", time.time(), ""]
# 看门狗耐心
watch_dog_patience = 5
# 请求任务
def _req_gpt(inputs, history, sys_prompt):
retry_op = retry_times_at_unknown_error
exceeded_cnt = 0
while True:
# watchdog error
if len(mutable) >= 2 and (time.time()-mutable[1]) > 5:
if len(mutable) >= 2 and (time.time()-mutable[1]) > watch_dog_patience:
raise RuntimeError("检测到程序终止。")
try:
# 【第一种情况】:顺利完成
@@ -191,6 +196,9 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
# 跨线程传递
mutable = [["", time.time(), "等待中"] for _ in range(n_frag)]
# 看门狗耐心
watch_dog_patience = 5
# 子线程任务
def _req_gpt(index, inputs, history, sys_prompt):
gpt_say = ""
@@ -199,7 +207,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
mutable[index][2] = "执行中"
while True:
# watchdog error
if len(mutable[index]) >= 2 and (time.time()-mutable[index][1]) > 5:
if len(mutable[index]) >= 2 and (time.time()-mutable[index][1]) > watch_dog_patience:
raise RuntimeError("检测到程序终止。")
try:
# 【第一种情况】:顺利完成
@@ -273,7 +281,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
# 在前端打印些好玩的东西
for thread_index, _ in enumerate(worker_done):
print_something_really_funny = "[ ...`"+mutable[thread_index][0][-scroller_max_len:].\
replace('\n', '').replace('```', '...').replace(
replace('\n', '').replace('`', '.').replace(
' ', '.').replace('<br/>', '.....').replace('$', '.')+"`... ]"
observe_win.append(print_something_really_funny)
# 在前端打印些好玩的东西
@@ -299,7 +307,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
gpt_res = f.result()
chatbot.append([inputs_show_user, gpt_res])
yield from update_ui(chatbot=chatbot, history=[]) # 刷新界面
time.sleep(0.3)
time.sleep(0.5)
return gpt_response_collection
@@ -469,14 +477,16 @@ def read_and_clean_pdf_text(fp):
'- ', '') for t in text_areas['blocks'] if 'lines' in t]
############################## <第 2 步,获取正文主字体> ##################################
fsize_statiscs = {}
for span in meta_span:
if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
fsize_statiscs[span[1]] += span[2]
main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
if REMOVE_FOOT_NOTE:
give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
try:
fsize_statiscs = {}
for span in meta_span:
if span[1] not in fsize_statiscs: fsize_statiscs[span[1]] = 0
fsize_statiscs[span[1]] += span[2]
main_fsize = max(fsize_statiscs, key=fsize_statiscs.get)
if REMOVE_FOOT_NOTE:
give_up_fize_threshold = main_fsize * REMOVE_FOOT_FFSIZE_PERCENT
except:
raise RuntimeError(f'抱歉, 我们暂时无法解析此PDF文档: {fp}')
############################## <第 3 步,切分和重新整合> ##################################
mega_sec = []
sec = []
@@ -591,11 +601,16 @@ 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]
@@ -642,7 +657,7 @@ class knowledge_archive_interface():
from toolbox import ProxyNetworkActivate
print('Checking Text2vec ...')
from langchain.embeddings.huggingface import HuggingFaceEmbeddings
with ProxyNetworkActivate(): # 临时地激活代理网络
with ProxyNetworkActivate('Download_LLM'): # 临时地激活代理网络
self.text2vec_large_chinese = HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
return self.text2vec_large_chinese
@@ -699,48 +714,95 @@ class knowledge_archive_interface():
self.threadLock.release()
return resp, prompt
def try_install_deps(deps):
@Singleton
class nougat_interface():
def __init__(self):
self.threadLock = threading.Lock()
def nougat_with_timeout(self, command, cwd, timeout=3600):
import subprocess
logging.info(f'正在执行命令 {command}')
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(self, fp, chatbot, history):
from toolbox import update_ui_lastest_msg
yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度:正在排队, 等待线程锁...",
chatbot=chatbot, history=history, delay=0)
self.threadLock.acquire()
import glob, threading, os
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)
yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度正在加载NOUGAT... 提示首次运行需要花费较长时间下载NOUGAT参数",
chatbot=chatbot, history=history, delay=0)
self.nougat_with_timeout(f'nougat --out "{os.path.abspath(dst)}" "{os.path.abspath(fp)}"', os.getcwd(), timeout=3600)
res = glob.glob(os.path.join(dst,'*.mmd'))
if len(res) == 0:
self.threadLock.release()
raise RuntimeError("Nougat解析论文失败。")
self.threadLock.release()
return res[0]
def try_install_deps(deps, reload_m=[]):
import subprocess, sys, importlib
for dep in deps:
import subprocess, sys
subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--user', dep])
import site
importlib.reload(site)
for m in reload_m:
importlib.reload(__import__(m))
class construct_html():
def __init__(self) -> None:
self.css = """
HTML_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 = """
TABLE_CSS = """
<div class="row table-row">
<div class="column table-cell">REPLACE_A</div>
<div class="column table-cell">REPLACE_B</div>
</div>
"""
"""
class construct_html():
def __init__(self) -> None:
self.css = HTML_CSS
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 = TABLE_CSS
from toolbox import markdown_convertion
tmp = tmp.replace('REPLACE_A', markdown_convertion(a))
tmp = tmp.replace('REPLACE_B', markdown_convertion(b))
@@ -748,6 +810,13 @@ class construct_html():
def save_file(self, file_name):
with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
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)
def get_plugin_arg(plugin_kwargs, key, default):
# 如果参数是空的
if (key in plugin_kwargs) and (plugin_kwargs[key] == ""): plugin_kwargs.pop(key)
# 正常情况
return plugin_kwargs.get(key, default)

View File

@@ -0,0 +1,70 @@
import time
import importlib
from toolbox import trimmed_format_exc, gen_time_str, get_log_folder
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
import multiprocessing
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
def try_make_module(code, chatbot):
module_file = 'gpt_fn_' + gen_time_str().replace('-','_')
fn_path = f'{get_log_folder(plugin_name="gen_plugin_verify")}/{module_file}.py'
with open(fn_path, 'w', encoding='utf8') as f: f.write(code)
promote_file_to_downloadzone(fn_path, chatbot=chatbot)
class_name = get_class_name(code)
manager = multiprocessing.Manager()
return_dict = manager.dict()
p = multiprocessing.Process(target=is_function_successfully_generated, args=(fn_path, class_name, return_dict))
# only has 10 seconds to run
p.start(); p.join(timeout=10)
if p.is_alive(): p.terminate(); p.join()
p.close()
return return_dict["success"], return_dict['traceback']
# check is_function_successfully_generated
def is_function_successfully_generated(fn_path, class_name, return_dict):
return_dict['success'] = False
return_dict['traceback'] = ""
try:
# Create a spec for the module
module_spec = importlib.util.spec_from_file_location('example_module', fn_path)
# Load the module
example_module = importlib.util.module_from_spec(module_spec)
module_spec.loader.exec_module(example_module)
# Now you can use the module
some_class = getattr(example_module, class_name)
# Now you can create an instance of the class
instance = some_class()
return_dict['success'] = True
return
except:
return_dict['traceback'] = trimmed_format_exc()
return
def subprocess_worker(code, file_path, return_dict):
return_dict['result'] = None
return_dict['success'] = False
return_dict['traceback'] = ""
try:
module_file = 'gpt_fn_' + gen_time_str().replace('-','_')
fn_path = f'{get_log_folder(plugin_name="gen_plugin_run")}/{module_file}.py'
with open(fn_path, 'w', encoding='utf8') as f: f.write(code)
class_name = get_class_name(code)
# Create a spec for the module
module_spec = importlib.util.spec_from_file_location('example_module', fn_path)
# Load the module
example_module = importlib.util.module_from_spec(module_spec)
module_spec.loader.exec_module(example_module)
# Now you can use the module
some_class = getattr(example_module, class_name)
# Now you can create an instance of the class
instance = some_class()
return_dict['result'] = instance.run(file_path)
return_dict['success'] = True
except:
return_dict['traceback'] = trimmed_format_exc()

View File

@@ -1,4 +1,4 @@
from toolbox import update_ui, update_ui_lastest_msg # 刷新Gradio前端界面
from toolbox import update_ui, update_ui_lastest_msg, get_log_folder
from toolbox import zip_folder, objdump, objload, promote_file_to_downloadzone
from .latex_toolbox import PRESERVE, TRANSFORM
from .latex_toolbox import set_forbidden_text, set_forbidden_text_begin_end, set_forbidden_text_careful_brace
@@ -363,7 +363,7 @@ def 编译Latex(chatbot, history, main_file_original, main_file_modified, work_f
if mode!='translate_zh':
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 使用latexdiff生成论文转化前后对比 ...', chatbot, history) # 刷新Gradio前端界面
print( f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex')
ok = compile_latex_with_timeout(f'latexdiff --encoding=utf8 --append-safecmd=subfile {work_folder_original}/{main_file_original}.tex {work_folder_modified}/{main_file_modified}.tex --flatten > {work_folder}/merge_diff.tex', os.getcwd())
yield from update_ui_lastest_msg(f'尝试第 {n_fix}/{max_try} 次编译, 正在编译对比PDF ...', chatbot, history) # 刷新Gradio前端界面
ok = compile_latex_with_timeout(f'pdflatex -interaction=batchmode -file-line-error merge_diff.tex', work_folder)
@@ -439,9 +439,9 @@ def write_html(sp_file_contents, sp_file_result, chatbot, project_folder):
trans = k
ch.add_row(a=orig, b=trans)
create_report_file_name = f"{gen_time_str()}.trans.html"
ch.save_file(create_report_file_name)
shutil.copyfile(pj('./gpt_log/', create_report_file_name), pj(project_folder, create_report_file_name))
promote_file_to_downloadzone(file=f'./gpt_log/{create_report_file_name}', chatbot=chatbot)
res = ch.save_file(create_report_file_name)
shutil.copyfile(res, pj(project_folder, create_report_file_name))
promote_file_to_downloadzone(file=res, chatbot=chatbot)
except:
from toolbox import trimmed_format_exc
print('writing html result failed:', trimmed_format_exc())

View File

@@ -256,6 +256,7 @@ def find_main_tex_file(file_manifest, mode):
canidates_score.append(0)
with open(texf, 'r', encoding='utf8', errors='ignore') as f:
file_content = f.read()
file_content = rm_comments(file_content)
for uw in unexpected_words:
if uw in file_content:
canidates_score[-1] -= 1
@@ -290,7 +291,11 @@ def find_tex_file_ignore_case(fp):
import glob
for f in glob.glob(dir_name+'/*.tex'):
base_name_s = os.path.basename(fp)
if base_name_s.lower() == base_name.lower(): return f
base_name_f = os.path.basename(f)
if base_name_s.lower() == base_name_f.lower(): return f
# 试着加上.tex后缀试试
if not base_name_s.endswith('.tex'): base_name_s+='.tex'
if base_name_s.lower() == base_name_f.lower(): return f
return None
def merge_tex_files_(project_foler, main_file, mode):
@@ -301,9 +306,9 @@ def merge_tex_files_(project_foler, main_file, mode):
for s in reversed([q for q in re.finditer(r"\\input\{(.*?)\}", main_file, re.M)]):
f = s.group(1)
fp = os.path.join(project_foler, f)
fp = find_tex_file_ignore_case(fp)
if fp:
with open(fp, 'r', encoding='utf-8', errors='replace') as fx: c = fx.read()
fp_ = find_tex_file_ignore_case(fp)
if fp_:
with open(fp_, 'r', encoding='utf-8', errors='replace') as fx: c = fx.read()
else:
raise RuntimeError(f'找不到{fp}Tex源文件缺失')
c = merge_tex_files_(project_foler, c, mode)
@@ -337,10 +342,33 @@ def merge_tex_files(project_foler, main_file, mode):
pattern_opt2 = re.compile(r"\\abstract\{(.*?)\}", flags=re.DOTALL)
match_opt1 = pattern_opt1.search(main_file)
match_opt2 = pattern_opt2.search(main_file)
if (match_opt1 is None) and (match_opt2 is None):
# "Cannot find paper abstract section!"
main_file = insert_abstract(main_file)
match_opt1 = pattern_opt1.search(main_file)
match_opt2 = pattern_opt2.search(main_file)
assert (match_opt1 is not None) or (match_opt2 is not None), "Cannot find paper abstract section!"
return main_file
insert_missing_abs_str = r"""
\begin{abstract}
The GPT-Academic program cannot find abstract section in this paper.
\end{abstract}
"""
def insert_abstract(tex_content):
if "\\maketitle" in tex_content:
# find the position of "\maketitle"
find_index = tex_content.index("\\maketitle")
# find the nearest ending line
end_line_index = tex_content.find("\n", find_index)
# insert "abs_str" on the next line
modified_tex = tex_content[:end_line_index+1] + '\n\n' + insert_missing_abs_str + '\n\n' + tex_content[end_line_index+1:]
return modified_tex
else:
return tex_content
"""
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
Post process
@@ -423,7 +451,7 @@ def compile_latex_with_timeout(command, cwd, timeout=60):
def merge_pdfs(pdf1_path, pdf2_path, output_path):
import PyPDF2
Percent = 0.8
Percent = 0.95
# Open the first PDF file
with open(pdf1_path, 'rb') as pdf1_file:
pdf1_reader = PyPDF2.PdfFileReader(pdf1_file)

View File

@@ -1,4 +1,106 @@
import time, threading, json
import time, logging, json, sys, struct
import numpy as np
from scipy.io.wavfile import WAVE_FORMAT
def write_numpy_to_wave(filename, rate, data, add_header=False):
"""
Write a NumPy array as a WAV file.
"""
def _array_tofile(fid, data):
# ravel gives a c-contiguous buffer
fid.write(data.ravel().view('b').data)
if hasattr(filename, 'write'):
fid = filename
else:
fid = open(filename, 'wb')
fs = rate
try:
dkind = data.dtype.kind
if not (dkind == 'i' or dkind == 'f' or (dkind == 'u' and
data.dtype.itemsize == 1)):
raise ValueError("Unsupported data type '%s'" % data.dtype)
header_data = b''
header_data += b'RIFF'
header_data += b'\x00\x00\x00\x00'
header_data += b'WAVE'
# fmt chunk
header_data += b'fmt '
if dkind == 'f':
format_tag = WAVE_FORMAT.IEEE_FLOAT
else:
format_tag = WAVE_FORMAT.PCM
if data.ndim == 1:
channels = 1
else:
channels = data.shape[1]
bit_depth = data.dtype.itemsize * 8
bytes_per_second = fs*(bit_depth // 8)*channels
block_align = channels * (bit_depth // 8)
fmt_chunk_data = struct.pack('<HHIIHH', format_tag, channels, fs,
bytes_per_second, block_align, bit_depth)
if not (dkind == 'i' or dkind == 'u'):
# add cbSize field for non-PCM files
fmt_chunk_data += b'\x00\x00'
header_data += struct.pack('<I', len(fmt_chunk_data))
header_data += fmt_chunk_data
# fact chunk (non-PCM files)
if not (dkind == 'i' or dkind == 'u'):
header_data += b'fact'
header_data += struct.pack('<II', 4, data.shape[0])
# check data size (needs to be immediately before the data chunk)
if ((len(header_data)-4-4) + (4+4+data.nbytes)) > 0xFFFFFFFF:
raise ValueError("Data exceeds wave file size limit")
if add_header:
fid.write(header_data)
# data chunk
fid.write(b'data')
fid.write(struct.pack('<I', data.nbytes))
if data.dtype.byteorder == '>' or (data.dtype.byteorder == '=' and
sys.byteorder == 'big'):
data = data.byteswap()
_array_tofile(fid, data)
if add_header:
# Determine file size and place it in correct
# position at start of the file.
size = fid.tell()
fid.seek(4)
fid.write(struct.pack('<I', size-8))
finally:
if not hasattr(filename, 'write'):
fid.close()
else:
fid.seek(0)
def is_speaker_speaking(vad, data, sample_rate):
# Function to detect if the speaker is speaking
# The WebRTC VAD only accepts 16-bit mono PCM audio,
# sampled at 8000, 16000, 32000 or 48000 Hz.
# A frame must be either 10, 20, or 30 ms in duration:
frame_duration = 30
n_bit_each = int(sample_rate * frame_duration / 1000)*2 # x2 because audio is 16 bit (2 bytes)
res_list = []
for t in range(len(data)):
if t!=0 and t % n_bit_each == 0:
res_list.append(vad.is_speech(data[t-n_bit_each:t], sample_rate))
info = ''.join(['^' if r else '.' for r in res_list])
info = info[:10]
if any(res_list):
return True, info
else:
return False, info
class AliyunASR():
@@ -12,14 +114,14 @@ 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 +138,6 @@ 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
@@ -67,12 +168,22 @@ class AliyunASR():
on_close=self.test_on_close,
callback_args=[uuid.hex]
)
timeout_limit_second = 20
r = sr.start(aformat="pcm",
timeout=timeout_limit_second,
enable_intermediate_result=True,
enable_punctuation_prediction=True,
enable_inverse_text_normalization=True)
import webrtcvad
vad = webrtcvad.Vad()
vad.set_mode(1)
is_previous_frame_transmitted = False # 上一帧是否有人说话
previous_frame_data = None
echo_cnt = 0 # 在没有声音之后继续向服务器发送n次音频数据
echo_cnt_max = 4 # 在没有声音之后继续向服务器发送n次音频数据
keep_alive_last_send_time = time.time()
while not self.stop:
# time.sleep(self.capture_interval)
audio = rad.read(uuid.hex)
@@ -80,12 +191,32 @@ class AliyunASR():
# convert to pcm file
temp_file = f'{temp_folder}/{uuid.hex}.pcm' #
dsdata = change_sample_rate(audio, rad.rate, NEW_SAMPLERATE) # 48000 --> 16000
io.wavfile.write(temp_file, NEW_SAMPLERATE, dsdata)
write_numpy_to_wave(temp_file, NEW_SAMPLERATE, dsdata)
# read pcm binary
with open(temp_file, "rb") as f: data = f.read()
# print('audio len:', len(audio), '\t ds len:', len(dsdata), '\t need n send:', len(data)//640)
slices = zip(*(iter(data),) * 640) # 640个字节为一组
for i in slices: sr.send_audio(bytes(i))
is_speaking, info = is_speaker_speaking(vad, data, NEW_SAMPLERATE)
if is_speaking or echo_cnt > 0:
# 如果话筒激活 / 如果处于回声收尾阶段
echo_cnt -= 1
if not is_previous_frame_transmitted: # 上一帧没有人声,但是我们把上一帧同样加上
if previous_frame_data is not None: data = previous_frame_data + data
if is_speaking:
echo_cnt = echo_cnt_max
slices = zip(*(iter(data),) * 640) # 640个字节为一组
for i in slices: sr.send_audio(bytes(i))
keep_alive_last_send_time = time.time()
is_previous_frame_transmitted = True
else:
is_previous_frame_transmitted = False
echo_cnt = 0
# 保持链接激活,即使没有声音,也根据时间间隔,发送一些音频片段给服务器
if time.time() - keep_alive_last_send_time > timeout_limit_second/2:
slices = zip(*(iter(data),) * 640) # 640个字节为一组
for i in slices: sr.send_audio(bytes(i))
keep_alive_last_send_time = time.time()
is_previous_frame_transmitted = True
self.audio_shape = info
else:
time.sleep(0.1)

View File

@@ -35,7 +35,7 @@ class RealtimeAudioDistribution():
def read(self, uuid):
if uuid in self.data:
res = self.data.pop(uuid)
print('\r read-', len(res), '-', max(res), end='', flush=True)
# print('\r read-', len(res), '-', max(res), end='', flush=True)
else:
res = None
return res

View File

@@ -1,16 +1,26 @@
from functools import lru_cache
from toolbox import gen_time_str
from toolbox import promote_file_to_downloadzone
from toolbox import write_history_to_file, promote_file_to_downloadzone
from toolbox import get_conf
from toolbox import ProxyNetworkActivate
from colorful import *
import requests
import random
from functools import lru_cache
import copy
import os
import math
class GROBID_OFFLINE_EXCEPTION(Exception): pass
def get_avail_grobid_url():
from toolbox import get_conf
GROBID_URLS, = get_conf('GROBID_URLS')
if len(GROBID_URLS) == 0: return None
try:
_grobid_url = random.choice(GROBID_URLS) # 随机负载均衡
if _grobid_url.endswith('/'): _grobid_url = _grobid_url.rstrip('/')
res = requests.get(_grobid_url+'/api/isalive')
with ProxyNetworkActivate('Connect_Grobid'):
res = requests.get(_grobid_url+'/api/isalive')
if res.text=='true': return _grobid_url
else: return None
except:
@@ -20,6 +30,142 @@ 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:
with ProxyNetworkActivate('Connect_Grobid'):
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
def produce_report_markdown(gpt_response_collection, meta, paper_meta_info, chatbot, fp, generated_conclusion_files):
# -=-=-=-=-=-=-=-= 写出第1个文件翻译前后混合 -=-=-=-=-=-=-=-=
res_path = write_history_to_file(meta + ["# Meta Translation" , paper_meta_info] + gpt_response_collection, file_basename=f"{gen_time_str()}translated_and_original.md", file_fullname=None)
promote_file_to_downloadzone(res_path, rename_file=os.path.basename(res_path)+'.md', chatbot=chatbot)
generated_conclusion_files.append(res_path)
# -=-=-=-=-=-=-=-= 写出第2个文件仅翻译后的文本 -=-=-=-=-=-=-=-=
translated_res_array = []
# 记录当前的大章节标题:
last_section_name = ""
for index, value in enumerate(gpt_response_collection):
# 先挑选偶数序列号:
if index % 2 != 0:
# 先提取当前英文标题:
cur_section_name = gpt_response_collection[index-1].split('\n')[0].split(" Part")[0]
# 如果index是1的话则直接使用first section name
if cur_section_name != last_section_name:
cur_value = cur_section_name + '\n'
last_section_name = copy.deepcopy(cur_section_name)
else:
cur_value = ""
# 再做一个小修改重新修改当前part的标题默认用英文的
cur_value += value
translated_res_array.append(cur_value)
res_path = write_history_to_file(meta + ["# Meta Translation" , paper_meta_info] + translated_res_array,
file_basename = f"{gen_time_str()}-translated_only.md",
file_fullname = None,
auto_caption = False)
promote_file_to_downloadzone(res_path, rename_file=os.path.basename(res_path)+'.md', chatbot=chatbot)
generated_conclusion_files.append(res_path)
return res_path
def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG):
from crazy_functions.crazy_utils import construct_html
from crazy_functions.crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
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=()))
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],
)
# -=-=-=-=-=-=-=-= 写出Markdown文件 -=-=-=-=-=-=-=-=
produce_report_markdown(gpt_response_collection, meta, paper_meta_info, chatbot, fp, generated_conclusion_files)
# -=-=-=-=-=-=-=-= 写出HTML文件 -=-=-=-=-=-=-=-=
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:
# 先提取当前英文标题:
cur_section_name = gpt_response_collection[i-1].split('\n')[0].split(" Part")[0]
cur_value = cur_section_name + "\n" + gpt_response_collection_html[i]
gpt_response_collection_html[i] = cur_value
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_conclusion_files.append(html_file)
promote_file_to_downloadzone(html_file, rename_file=os.path.basename(html_file), chatbot=chatbot)

View File

@@ -1,5 +1,6 @@
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file, get_conf
from toolbox import update_ui, get_log_folder
from toolbox import write_history_to_file, promote_file_to_downloadzone
from toolbox import CatchException, report_execption, get_conf
import re, requests, unicodedata, os
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
def download_arxiv_(url_pdf):
@@ -28,7 +29,7 @@ def download_arxiv_(url_pdf):
if k in other_info['comment']:
title = k + ' ' + title
download_dir = './gpt_log/arxiv/'
download_dir = get_log_folder(plugin_name='arxiv')
os.makedirs(download_dir, exist_ok=True)
title_str = title.replace('?', '')\
@@ -40,9 +41,6 @@ def download_arxiv_(url_pdf):
requests_pdf_url = url_pdf
file_path = download_dir+title_str
# if os.path.exists(file_path):
# print('返回缓存文件')
# return './gpt_log/arxiv/'+title_str
print('下载中')
proxies, = get_conf('proxies')
@@ -61,7 +59,7 @@ def download_arxiv_(url_pdf):
.replace('\n', '')\
.replace(' ', ' ')\
.replace(' ', ' ')
return './gpt_log/arxiv/'+title_str, other_info
return file_path, other_info
def get_name(_url_):
@@ -184,11 +182,10 @@ def 下载arxiv论文并翻译摘要(txt, llm_kwargs, plugin_kwargs, chatbot, hi
chatbot[-1] = (i_say_show_user, gpt_say)
history.append(i_say_show_user); history.append(gpt_say)
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
# 写入文件
import shutil
# 重置文件的创建时间
shutil.copyfile(pdf_path, f'./gpt_log/{os.path.basename(pdf_path)}'); os.remove(pdf_path)
res = write_results_to_file(history)
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
promote_file_to_downloadzone(pdf_path, chatbot=chatbot)
chatbot.append(("完成了吗?", res + "\n\nPDF文件也已经下载"))
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面

View File

@@ -1,138 +0,0 @@
import threading
from request_llm.bridge_all import predict_no_ui_long_connection
from toolbox import update_ui
from toolbox import CatchException, write_results_to_file, report_execption
from .crazy_utils import breakdown_txt_to_satisfy_token_limit
def extract_code_block_carefully(txt):
splitted = txt.split('```')
n_code_block_seg = len(splitted) - 1
if n_code_block_seg <= 1: return txt
# 剩下的情况都开头除去 ``` 结尾除去一次 ```
txt_out = '```'.join(splitted[1:-1])
return txt_out
def break_txt_into_half_at_some_linebreak(txt):
lines = txt.split('\n')
n_lines = len(lines)
pre = lines[:(n_lines//2)]
post = lines[(n_lines//2):]
return "\n".join(pre), "\n".join(post)
@CatchException
def 全项目切换英文(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys_prompt, web_port):
# 第1步清空历史以免输入溢出
history = []
# 第2步尝试导入依赖如果缺少依赖则给出安装建议
try:
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 tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 第3步集合文件
import time, glob, os, shutil, re
os.makedirs('gpt_log/generated_english_version', exist_ok=True)
os.makedirs('gpt_log/generated_english_version/crazy_functions', exist_ok=True)
file_manifest = [f for f in glob.glob('./*.py') if ('test_project' not in f) and ('gpt_log' not in f)] + \
[f for f in glob.glob('./crazy_functions/*.py') if ('test_project' not in f) and ('gpt_log' not in f)]
# file_manifest = ['./toolbox.py']
i_say_show_user_buffer = []
# 第4步随便显示点什么防止卡顿的感觉
for index, fp in enumerate(file_manifest):
# if 'test_project' in fp: continue
with open(fp, 'r', encoding='utf-8', errors='replace') as f:
file_content = f.read()
i_say_show_user =f'[{index}/{len(file_manifest)}] 接下来请将以下代码中包含的所有中文转化为英文,只输出转化后的英文代码,请用代码块输出代码: {os.path.abspath(fp)}'
i_say_show_user_buffer.append(i_say_show_user)
chatbot.append((i_say_show_user, "[Local Message] 等待多线程操作,中间过程不予显示."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 第5步Token限制下的截断与处理
MAX_TOKEN = 3000
from request_llm.bridge_all import model_info
enc = model_info["gpt-3.5-turbo"]['tokenizer']
def get_token_fn(txt): return len(enc.encode(txt, disallowed_special=()))
# 第6步任务函数
mutable_return = [None for _ in file_manifest]
observe_window = [[""] for _ in file_manifest]
def thread_worker(fp,index):
if index > 10:
time.sleep(60)
print('Openai 限制免费用户每分钟20次请求降低请求频率中。')
with open(fp, 'r', encoding='utf-8', errors='replace') as f:
file_content = f.read()
i_say_template = lambda fp, file_content: f'接下来请将以下代码中包含的所有中文转化为英文,只输出代码,文件名是{fp},文件代码是 ```{file_content}```'
try:
gpt_say = ""
# 分解代码文件
file_content_breakdown = breakdown_txt_to_satisfy_token_limit(file_content, get_token_fn, MAX_TOKEN)
for file_content_partial in file_content_breakdown:
i_say = i_say_template(fp, file_content_partial)
# # ** gpt request **
gpt_say_partial = predict_no_ui_long_connection(inputs=i_say, llm_kwargs=llm_kwargs, history=[], sys_prompt=sys_prompt, observe_window=observe_window[index])
gpt_say_partial = extract_code_block_carefully(gpt_say_partial)
gpt_say += gpt_say_partial
mutable_return[index] = gpt_say
except ConnectionAbortedError as token_exceed_err:
print('至少一个线程任务Token溢出而失败', e)
except Exception as e:
print('至少一个线程任务意外失败', e)
# 第7步所有线程同时开始执行任务函数
handles = [threading.Thread(target=thread_worker, args=(fp,index)) for index, fp in enumerate(file_manifest)]
for h in handles:
h.daemon = True
h.start()
chatbot.append(('开始了吗?', f'多线程操作已经开始'))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 第8步循环轮询各个线程是否执行完毕
cnt = 0
while True:
cnt += 1
time.sleep(0.2)
th_alive = [h.is_alive() for h in handles]
if not any(th_alive): break
# 更好的UI视觉效果
observe_win = []
for thread_index, alive in enumerate(th_alive):
observe_win.append("[ ..."+observe_window[thread_index][0][-60:].replace('\n','').replace('```','...').replace(' ','.').replace('<br/>','.....').replace('$','.')+"... ]")
stat = [f'执行中: {obs}\n\n' if alive else '已完成\n\n' for alive, obs in zip(th_alive, observe_win)]
stat_str = ''.join(stat)
chatbot[-1] = (chatbot[-1][0], f'多线程操作已经开始,完成情况: \n\n{stat_str}' + ''.join(['.']*(cnt%10+1)))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 第9步把结果写入文件
for index, h in enumerate(handles):
h.join() # 这里其实不需要join了肯定已经都结束了
fp = file_manifest[index]
gpt_say = mutable_return[index]
i_say_show_user = i_say_show_user_buffer[index]
where_to_relocate = f'gpt_log/generated_english_version/{fp}'
if gpt_say is not None:
with open(where_to_relocate, 'w+', encoding='utf-8') as f:
f.write(gpt_say)
else: # 失败
shutil.copyfile(file_manifest[index], where_to_relocate)
chatbot.append((i_say_show_user, f'[Local Message] 已完成{os.path.abspath(fp)}的转化,\n\n存入{os.path.abspath(where_to_relocate)}'))
history.append(i_say_show_user); history.append(gpt_say)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
time.sleep(1)
# 第10步备份一个文件
res = write_results_to_file(history)
chatbot.append(("生成一份任务执行报告", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

View File

@@ -0,0 +1,252 @@
# 本源代码中, ⭐ = 关键步骤
"""
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
Testing:
- Crop the image, keeping the bottom half.
- Swap the blue channel and red channel of the image.
- Convert the image to grayscale.
- Convert the CSV file to an Excel spreadsheet.
"""
from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder
from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_lastest_msg
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
from .crazy_utils import input_clipping, try_install_deps
from crazy_functions.gen_fns.gen_fns_shared import is_function_successfully_generated
from crazy_functions.gen_fns.gen_fns_shared import get_class_name
from crazy_functions.gen_fns.gen_fns_shared import subprocess_worker
from crazy_functions.gen_fns.gen_fns_shared import try_make_module
import os
import time
import glob
import multiprocessing
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 world-class 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. You need to replace `...` with valid packages, do not give `...` in your answer!"
)
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 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 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 函数动态生成(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
"""
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
llm_kwargs gpt模型参数如温度和top_p等一般原样传递下去就行
plugin_kwargs 插件模型的参数,暂时没有用武之地
chatbot 聊天显示框的句柄,用于显示给用户
history 聊天历史,前情提要
system_prompt 给gpt的静默提醒
web_port 当前软件运行的端口号
"""
# 清空历史
history = []
# 基本信息:功能、贡献者
chatbot.append(["正在启动: 插件动态生成插件", "插件动态生成, 执行开始, 作者Binary-Husky."])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# ⭐ 文件上传区是否有东西
# 1. 如果有文件: 作为函数参数
# 2. 如果没有文件需要用GPT提取参数 (太懒了,以后再写,虚空终端已经实现了类似的代码)
file_list = []
if get_plugin_arg(plugin_kwargs, key="file_path_arg", default=False):
file_path = get_plugin_arg(plugin_kwargs, key="file_path_arg", default=None)
file_list.append(file_path)
yield from update_ui_lastest_msg(f"当前文件: {file_path}", chatbot, history, 1)
elif have_any_recent_upload_files(chatbot):
file_dir = get_recent_file_prompt_support(chatbot)
file_list = glob.glob(os.path.join(file_dir, '**/*'), recursive=True)
yield from update_ui_lastest_msg(f"当前文件处理列表: {file_list}", chatbot, history, 1)
else:
chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
return # 2. 如果没有文件
if len(file_list) == 0:
chatbot.append(["文件检索", "没有发现任何近期上传的文件。"])
yield from update_ui_lastest_msg("没有发现任何近期上传的文件。", chatbot, history, 1)
return # 2. 如果没有文件
# 读取文件
file_type = file_list[0].split('.')[-1]
# 粗心检查
if is_the_upload_folder(txt):
yield from update_ui_lastest_msg(f"请在输入框内填写需求, 然后再次点击该插件! 至于您的文件,不用担心, 文件路径 {txt} 已经被记忆. ", chatbot, history, 1)
return
# 开始干正事
MAX_TRY = 3
for j in range(MAX_TRY): # 最多重试5次
traceback = ""
try:
# ⭐ 开始啦
code, installation_advance, txt, file_type, llm_kwargs, chatbot, history = \
yield from gpt_interact_multi_step(txt, file_type, llm_kwargs, chatbot, history)
chatbot.append(["代码生成阶段结束", ""])
yield from update_ui_lastest_msg(f"正在验证上述代码的有效性 ...", chatbot, history, 1)
# ⭐ 分离代码块
code = get_code_block(code)
# ⭐ 检查模块
ok, traceback = try_make_module(code, chatbot)
# 搞定代码生成
if ok: break
except Exception as e:
if not traceback: traceback = trimmed_format_exc()
# 处理异常
if not traceback: traceback = trimmed_format_exc()
yield from update_ui_lastest_msg(f"{j+1}/{MAX_TRY} 次代码生成尝试, 失败了~ 别担心, 我们5秒后再试一次... \n\n此次我们的错误追踪是\n```\n{traceback}\n```\n", chatbot, history, 5)
# 代码生成结束, 开始执行
TIME_LIMIT = 15
yield from update_ui_lastest_msg(f"开始创建新进程并执行代码! 时间限制 {TIME_LIMIT} 秒. 请等待任务完成... ", chatbot, history, 1)
manager = multiprocessing.Manager()
return_dict = manager.dict()
# ⭐ 到最后一步了,开始逐个文件进行处理
for file_path in file_list:
if os.path.exists(file_path):
chatbot.append([f"正在处理文件: {file_path}", f"请稍等..."])
chatbot = for_immediate_show_off_when_possible(file_type, file_path, chatbot)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
else:
continue
# ⭐⭐⭐ subprocess_worker ⭐⭐⭐
p = multiprocessing.Process(target=subprocess_worker, args=(code, file_path, return_dict))
# ⭐ 开始执行时间限制TIME_LIMIT
p.start(); p.join(timeout=TIME_LIMIT)
if p.is_alive(): p.terminate(); p.join()
p.close()
res = return_dict['result']
success = return_dict['success']
traceback = return_dict['traceback']
if not success:
if not traceback: traceback = trimmed_format_exc()
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

View File

@@ -1,4 +1,4 @@
from toolbox import CatchException, update_ui, get_conf, select_api_key
from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
import datetime
@@ -33,7 +33,7 @@ def gen_image(llm_kwargs, prompt, resolution="256x256"):
raise RuntimeError(response.content.decode())
# 文件保存到本地
r = requests.get(image_url, proxies=proxies)
file_path = 'gpt_log/image_gen/'
file_path = f'{get_log_folder()}/image_gen/'
os.makedirs(file_path, exist_ok=True)
file_name = 'Image' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.png'
with open(file_path+file_name, 'wb+') as f: f.write(r.content)

View File

@@ -1,4 +1,4 @@
from toolbox import CatchException, update_ui, promote_file_to_downloadzone
from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
import re
@@ -10,8 +10,8 @@ def write_chat_to_file(chatbot, history=None, file_name=None):
import time
if file_name is None:
file_name = 'chatGPT对话历史' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.html'
os.makedirs('./gpt_log/', exist_ok=True)
with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
fp = os.path.join(get_log_folder(), file_name)
with open(fp, 'w', encoding='utf8') as f:
from themes.theme import advanced_css
f.write(f'<!DOCTYPE html><head><meta charset="utf-8"><title>对话历史</title><style>{advanced_css}</style></head>')
for i, contents in enumerate(chatbot):
@@ -29,8 +29,8 @@ def write_chat_to_file(chatbot, history=None, file_name=None):
for h in history:
f.write("\n>>>" + h)
f.write('</code>')
promote_file_to_downloadzone(f'./gpt_log/{file_name}', rename_file=file_name, chatbot=chatbot)
return '对话历史写入:' + os.path.abspath(f'./gpt_log/{file_name}')
promote_file_to_downloadzone(fp, rename_file=file_name, chatbot=chatbot)
return '对话历史写入:' + fp
def gen_file_preview(file_name):
try:
@@ -106,7 +106,7 @@ def 载入对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
if not success:
if txt == "": txt = '空空如也的输入栏'
import glob
local_history = "<br/>".join(["`"+hide_cwd(f)+f" ({gen_file_preview(f)})"+"`" for f in glob.glob(f'gpt_log/**/chatGPT对话历史*.html', recursive=True)])
local_history = "<br/>".join(["`"+hide_cwd(f)+f" ({gen_file_preview(f)})"+"`" for f in glob.glob(f'{get_log_folder()}/**/chatGPT对话历史*.html', recursive=True)])
chatbot.append([f"正在查找对话历史文件html格式: {txt}", f"找不到任何html文件: {txt}。但本地存储了以下历史文件,您可以将任意一个文件路径粘贴到输入区,然后重试:<br/>{local_history}"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -132,8 +132,8 @@ def 删除所有本地对话历史记录(txt, llm_kwargs, plugin_kwargs, chatbot
"""
import glob, os
local_history = "<br/>".join(["`"+hide_cwd(f)+"`" for f in glob.glob(f'gpt_log/**/chatGPT对话历史*.html', recursive=True)])
for f in glob.glob(f'gpt_log/**/chatGPT对话历史*.html', recursive=True):
local_history = "<br/>".join(["`"+hide_cwd(f)+"`" for f in glob.glob(f'{get_log_folder()}/**/chatGPT对话历史*.html', recursive=True)])
for f in glob.glob(f'{get_log_folder()}/**/chatGPT对话历史*.html', recursive=True):
os.remove(f)
chatbot.append([f"删除所有历史对话文件", f"已删除<br/>{local_history}"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

View File

@@ -1,5 +1,6 @@
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import CatchException, report_execption
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
fast_debug = False
@@ -71,11 +72,13 @@ def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot
history.extend([i_say,gpt_say])
this_paper_history.extend([i_say,gpt_say])
res = write_results_to_file(history)
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
res = write_results_to_file(history)
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("所有文件都总结完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

View File

@@ -1,5 +1,6 @@
from toolbox import CatchException, report_execption, select_api_key, update_ui, write_results_to_file, get_conf
from toolbox import CatchException, report_execption, select_api_key, update_ui, get_conf
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from toolbox import write_history_to_file, promote_file_to_downloadzone, get_log_folder
def split_audio_file(filename, split_duration=1000):
"""
@@ -15,7 +16,7 @@ def split_audio_file(filename, split_duration=1000):
"""
from moviepy.editor import AudioFileClip
import os
os.makedirs('gpt_log/mp3/cut/', exist_ok=True) # 创建存储切割音频的文件夹
os.makedirs(f"{get_log_folder(plugin_name='audio')}/mp3/cut/", exist_ok=True) # 创建存储切割音频的文件夹
# 读取音频文件
audio = AudioFileClip(filename)
@@ -31,8 +32,8 @@ def split_audio_file(filename, split_duration=1000):
start_time = split_points[i]
end_time = split_points[i + 1]
split_audio = audio.subclip(start_time, end_time)
split_audio.write_audiofile(f"gpt_log/mp3/cut/{filename[0]}_{i}.mp3")
filelist.append(f"gpt_log/mp3/cut/{filename[0]}_{i}.mp3")
split_audio.write_audiofile(f"{get_log_folder(plugin_name='audio')}/mp3/cut/{filename[0]}_{i}.mp3")
filelist.append(f"{get_log_folder(plugin_name='audio')}/mp3/cut/{filename[0]}_{i}.mp3")
audio.close()
return filelist
@@ -52,7 +53,7 @@ def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history):
'Authorization': f"Bearer {api_key}"
}
os.makedirs('gpt_log/mp3/', exist_ok=True)
os.makedirs(f"{get_log_folder(plugin_name='audio')}/mp3/", exist_ok=True)
for index, fp in enumerate(file_manifest):
audio_history = []
# 提取文件扩展名
@@ -60,8 +61,8 @@ def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history):
# 提取视频中的音频
if ext not in [".mp3", ".wav", ".m4a", ".mpga"]:
audio_clip = AudioFileClip(fp)
audio_clip.write_audiofile(f'gpt_log/mp3/output{index}.mp3')
fp = f'gpt_log/mp3/output{index}.mp3'
audio_clip.write_audiofile(f"{get_log_folder(plugin_name='audio')}/mp3/output{index}.mp3")
fp = f"{get_log_folder(plugin_name='audio')}/mp3/output{index}.mp3"
# 调用whisper模型音频转文字
voice = split_audio_file(fp)
for j, i in enumerate(voice):
@@ -113,18 +114,19 @@ def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history):
history=audio_history,
sys_prompt="总结文章。"
)
history.extend([i_say, gpt_say])
audio_history.extend([i_say, gpt_say])
res = write_results_to_file(history)
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append((f"{index + 1}段音频完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 删除中间文件夹
import shutil
shutil.rmtree('gpt_log/mp3')
res = write_results_to_file(history)
shutil.rmtree(f"{get_log_folder(plugin_name='audio')}/mp3")
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("所有音频都总结完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history)

View File

@@ -1,7 +1,7 @@
import glob, time, os, re
import glob, time, os, re, logging
from toolbox import update_ui, trimmed_format_exc, gen_time_str, disable_auto_promotion
from toolbox import CatchException, report_execption, write_history_to_file
from toolbox import promote_file_to_downloadzone, get_log_folder
from toolbox import CatchException, report_execption, get_log_folder
from toolbox import write_history_to_file, promote_file_to_downloadzone
fast_debug = False
class PaperFileGroup():
@@ -34,7 +34,7 @@ class PaperFileGroup():
self.sp_file_contents.append(segment)
self.sp_file_index.append(index)
self.sp_file_tag.append(self.file_paths[index] + f".part-{j}.md")
print('Segmentation: done')
logging.info('Segmentation: done')
def merge_result(self):
self.file_result = ["" for _ in range(len(self.file_paths))]
@@ -101,7 +101,7 @@ def 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, ch
pfg.merge_result()
pfg.write_result(language)
except:
print(trimmed_format_exc())
logging.error(trimmed_format_exc())
# <-------- 整理结果,退出 ---------->
create_report_file_name = gen_time_str() + f"-chatgpt.md"
@@ -121,7 +121,7 @@ def get_files_from_everything(txt, preference=''):
proxies, = get_conf('proxies')
# 网络的远程文件
if preference == 'Github':
print('正在从github下载资源 ...')
logging.info('正在从github下载资源 ...')
if not txt.endswith('.md'):
# Make a request to the GitHub API to retrieve the repository information
url = txt.replace("https://github.com/", "https://api.github.com/repos/") + '/readme'

View File

@@ -1,5 +1,6 @@
from toolbox import update_ui, promote_file_to_downloadzone, gen_time_str
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import CatchException, report_execption
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from .crazy_utils import read_and_clean_pdf_text
from .crazy_utils import input_clipping
@@ -99,8 +100,8 @@ do not have too much repetitive information, numerical values using the original
_, final_results = input_clipping("", final_results, max_token_limit=3200)
yield from update_ui(chatbot=chatbot, history=final_results) # 注意这里的历史记录被替代了
res = write_results_to_file(file_write_buffer, file_name=gen_time_str())
promote_file_to_downloadzone(res.split('\t')[-1], chatbot=chatbot)
res = write_history_to_file(file_write_buffer)
promote_file_to_downloadzone(res, chatbot=chatbot)
yield from update_ui(chatbot=chatbot, history=final_results) # 刷新界面

View File

@@ -1,6 +1,7 @@
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import CatchException, report_execption
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from toolbox import write_history_to_file, promote_file_to_downloadzone
fast_debug = False
@@ -115,7 +116,8 @@ def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbo
chatbot[-1] = (i_say, gpt_say)
history.append(i_say); history.append(gpt_say)
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
res = write_results_to_file(history)
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面

View File

@@ -0,0 +1,115 @@
from toolbox import CatchException, report_execption, get_log_folder, 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, promote_file_to_downloadzone
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, translate_pdf
from colorful import *
import copy
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 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 = 1024
generated_conclusion_files = []
generated_html_files = []
DST_LANG = "中文"
from crazy_functions.crazy_utils import nougat_interface, construct_html
nougat_handle = nougat_interface()
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 = yield from nougat_handle.NOUGAT_parse_pdf(fp, chatbot, history)
promote_file_to_downloadzone(fpp, rename_file=os.path.basename(fpp)+'.nougat.mmd', chatbot=chatbot)
with open(fpp, 'r', encoding='utf8') as f:
article_content = f.readlines()
article_dict = markdown_to_dict(article_content)
logging.info(article_dict)
yield from translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG)
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

View File

@@ -1,12 +1,12 @@
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import CatchException, report_execption, get_log_folder, 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 toolbox import write_history_to_file, promote_file_to_downloadzone
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 .pdf_fns.parse_pdf import parse_pdf, get_avail_grobid_url, translate_pdf
from colorful import *
import glob
import copy
import os
import math
@@ -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
@@ -57,115 +58,35 @@ 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
import copy, json
TOKEN_LIMIT_PER_FRAGMENT = 1024
generated_conclusion_files = []
generated_html_files = []
DST_LANG = "中文"
from crazy_functions.crazy_utils import construct_html
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)
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)
grobid_json_res = os.path.join(get_log_folder(), gen_time_str() + "grobid.json")
with open(grobid_json_res, 'w+', encoding='utf8') as f:
f.write(json.dumps(article_dict, indent=4, ensure_ascii=False))
promote_file_to_downloadzone(grobid_json_res, chatbot=chatbot)
if article_dict is None: raise RuntimeError("解析PDF失败请检查PDF是否损坏。")
yield from translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG)
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
def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
"""
此函数已经弃用
"""
import copy
TOKEN_LIMIT_PER_FRAGMENT = 1280
TOKEN_LIMIT_PER_FRAGMENT = 1024
generated_conclusion_files = []
generated_html_files = []
from crazy_functions.crazy_utils import construct_html
for index, fp in enumerate(file_manifest):
# 读取PDF文件
file_content, page_one = read_and_clean_pdf_text(fp)
@@ -216,10 +137,11 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
final = ["一、论文概况\n\n---\n\n", paper_meta_info.replace('# ', '### ') + '\n\n---\n\n', "二、论文翻译", ""]
final.extend(gpt_response_collection_md)
create_report_file_name = f"{os.path.basename(fp)}.trans.md"
res = write_results_to_file(final, file_name=create_report_file_name)
res = write_history_to_file(final, create_report_file_name)
promote_file_to_downloadzone(res, chatbot=chatbot)
# 更新UI
generated_conclusion_files.append(f'./gpt_log/{create_report_file_name}')
generated_conclusion_files.append(f'{get_log_folder()}/{create_report_file_name}')
chatbot.append((f"{fp}完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -261,49 +183,3 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
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)

View File

@@ -1,5 +1,6 @@
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import CatchException, report_execption
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
fast_debug = False
@@ -27,7 +28,8 @@ def 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
if not fast_debug: time.sleep(2)
if not fast_debug:
res = write_results_to_file(history)
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面

View File

@@ -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]):

View File

@@ -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]):

View File

@@ -24,12 +24,13 @@ 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://www.nature.com/articles/s41586-019-1724-z.pdf
- 「生成一张图片,图中鲜花怒放,绿草如茵,用插件实现。
- 「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://openreview.net/pdf?id=rJl0r3R9KX
- 「把Arxiv论文翻译成中文PDFarxiv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READMEGithub网址是https://github.com/facebookresearch/co-tracker」
- 「给爷翻译Arxiv论文arxiv论文的ID是1812.10695,记得用插件,不要自己瞎搞!
- 「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"
- 「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"
- 「请调用插件解析python源代码项目代码我刚刚打包拖到上传区了
- 「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。
@@ -45,7 +46,7 @@ explain_msg = """
from pydantic import BaseModel, Field
from typing import List
from toolbox import CatchException, update_ui, gen_time_str
from toolbox import CatchException, update_ui, is_the_upload_folder
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
@@ -111,7 +112,7 @@ def 虚空终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
# 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:
if is_the_upload_folder(txt):
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。"

View File

@@ -1,5 +1,6 @@
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import CatchException, report_execption
from toolbox import write_history_to_file, promote_file_to_downloadzone
fast_debug = True
@@ -110,7 +111,8 @@ def ipynb解释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbo
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# <-------- 写入文件,退出 ---------->
res = write_results_to_file(history)
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

View File

@@ -1,12 +1,13 @@
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import update_ui, promote_file_to_downloadzone, disable_auto_promotion
from toolbox import CatchException, report_execption, write_history_to_file
from .crazy_utils import input_clipping
def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
import os, copy
from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
msg = '正常'
disable_auto_promotion(chatbot=chatbot)
summary_batch_isolation = True
inputs_array = []
inputs_show_user_array = []
@@ -22,7 +23,7 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
file_content = f.read()
prefix = "接下来请你逐文件分析下面的工程" if index==0 else ""
i_say = prefix + f'请对下面的程序文件做一个概述文件名是{os.path.relpath(fp, project_folder)},文件代码是 ```{file_content}```'
i_say_show_user = prefix + f'[{index}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {os.path.abspath(fp)}'
i_say_show_user = prefix + f'[{index}/{len(file_manifest)}] 请对下面的程序文件做一个概述: {fp}'
# 装载请求内容
inputs_array.append(i_say)
inputs_show_user_array.append(i_say_show_user)
@@ -43,7 +44,8 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
# 全部文件解析完成,结果写入文件,准备对工程源代码进行汇总分析
report_part_1 = copy.deepcopy(gpt_response_collection)
history_to_return = report_part_1
res = write_results_to_file(report_part_1)
res = write_history_to_file(report_part_1)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成?", "逐个文件分析已完成。" + res + "\n\n正在开始汇总。"))
yield from update_ui(chatbot=chatbot, history=history_to_return) # 刷新界面
@@ -97,7 +99,8 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
############################## <END> ##################################
history_to_return.extend(report_part_2)
res = write_results_to_file(history_to_return)
res = write_history_to_file(history_to_return)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history_to_return) # 刷新界面
@@ -106,9 +109,8 @@ def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs,
def 解析项目本身(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
history = [] # 清空历史,以免输入溢出
import glob
file_manifest = [f for f in glob.glob('./*.py') if ('test_project' not in f) and ('gpt_log' not in f)] + \
[f for f in glob.glob('./crazy_functions/*.py') if ('test_project' not in f) and ('gpt_log' not in f)]+ \
[f for f in glob.glob('./request_llm/*.py') if ('test_project' not in f) and ('gpt_log' not in f)]
file_manifest = [f for f in glob.glob('./*.py')] + \
[f for f in glob.glob('./*/*.py')]
project_folder = './'
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何python文件: {txt}")
@@ -134,6 +136,23 @@ def 解析一个Python项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@CatchException
def 解析一个Matlab项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
history = [] # 清空历史,以免输入溢出
import glob, os
if os.path.exists(txt):
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
report_execption(chatbot, history, a = f"解析Matlab项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.m', recursive=True)]
if len(file_manifest) == 0:
report_execption(chatbot, history, a = f"解析Matlab项目: {txt}", b = f"找不到任何`.m`源文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@CatchException
def 解析一个C项目的头文件(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):

View File

@@ -6,6 +6,7 @@ import threading, time
import numpy as np
from .live_audio.aliyunASR import AliyunASR
import json
import re
class WatchDog():
def __init__(self, timeout, bark_fn, interval=3, msg="") -> None:
@@ -38,10 +39,22 @@ def chatbot2history(chatbot):
history = []
for c in chatbot:
for q in c:
if q not in ["[请讲话]", "[等待GPT响应]", "[正在等您说完问题]"]:
if q in ["[ 请讲话 ]", "[ 等待GPT响应 ]", "[ 正在等您说完问题 ]"]:
continue
elif q.startswith("[ 正在等您说完问题 ]"):
continue
else:
history.append(q.strip('<div class="markdown-body">').strip('</div>').strip('<p>').strip('</p>'))
return history
def visualize_audio(chatbot, audio_shape):
if len(chatbot) == 0: chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
chatbot[-1] = list(chatbot[-1])
p1 = ''
p2 = ''
chatbot[-1][-1] = re.sub(p1+r'(.*)'+p2, '', chatbot[-1][-1])
chatbot[-1][-1] += (p1+f"`{audio_shape}`"+p2)
class AsyncGptTask():
def __init__(self) -> None:
self.observe_future = []
@@ -80,9 +93,10 @@ 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.audio_shape = "" # 音频的可视化表现, 由 audio_convertion_thread() 写入
self.event_on_result_chg = threading.Event()
self.event_on_entence_end = threading.Event()
self.event_on_commit_question = threading.Event()
@@ -117,7 +131,7 @@ class InterviewAssistant(AliyunASR):
def begin(self, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
# main plugin function
self.init(chatbot)
chatbot.append(["[请讲话]", "[正在等您说完问题]"])
chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
self.plugin_wd.begin_watch()
self.agt = AsyncGptTask()
@@ -132,7 +146,7 @@ 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 +158,11 @@ 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
@@ -153,14 +171,18 @@ class InterviewAssistant(AliyunASR):
self.commit_wd.begin_watch()
chatbot[-1] = list(chatbot[-1])
chatbot[-1] = [self.buffered_sentence, "[等待GPT响应]"]
chatbot[-1] = [self.buffered_sentence, "[ 等待GPT响应 ]"]
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# add gpt task 创建子线程请求gpt避免线程阻塞
history = chatbot2history(chatbot)
self.agt.add_async_gpt_task(self.buffered_sentence, len(chatbot)-1, llm_kwargs, history, system_prompt)
self.buffered_sentence = ""
chatbot.append(["[请讲话]", "[正在等您说完问题]"])
chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
if not self.event_on_result_chg.is_set() and not self.event_on_entence_end.is_set() and not self.event_on_commit_question.is_set():
visualize_audio(chatbot, self.audio_shape)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
if len(self.stop_msg) != 0:
@@ -179,7 +201,7 @@ def 语音助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
import nls
from scipy import io
except:
chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"])
chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return

View File

@@ -1,7 +1,7 @@
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import CatchException, report_execption
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
fast_debug = False
def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
@@ -17,32 +17,29 @@ def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbo
chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user, llm_kwargs, chatbot, history=[], sys_prompt=system_prompt) # 带超时倒计时
chatbot[-1] = (i_say_show_user, gpt_say)
history.append(i_say_show_user); history.append(gpt_say)
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
if not fast_debug: time.sleep(2)
msg = '正常'
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user, llm_kwargs, chatbot, history=[], sys_prompt=system_prompt) # 带超时倒计时
chatbot[-1] = (i_say_show_user, gpt_say)
history.append(i_say_show_user); history.append(gpt_say)
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
time.sleep(2)
all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)])
i_say = f'根据以上你自己的分析,对全文进行概括,用学术性语言写一段中文摘要,然后再写一段英文摘要(包括{all_file})。'
chatbot.append((i_say, "[Local Message] waiting gpt response."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
if not fast_debug:
msg = '正常'
# ** gpt request **
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say, llm_kwargs, chatbot, history=history, sys_prompt=system_prompt) # 带超时倒计时
msg = '正常'
# ** gpt request **
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say, llm_kwargs, chatbot, history=history, sys_prompt=system_prompt) # 带超时倒计时
chatbot[-1] = (i_say, gpt_say)
history.append(i_say); history.append(gpt_say)
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
res = write_results_to_file(history)
chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
chatbot[-1] = (i_say, gpt_say)
history.append(i_say); history.append(gpt_say)
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
res = write_history_to_file(history)
promote_file_to_downloadzone(res, chatbot=chatbot)
chatbot.append(("完成了吗?", res))
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面

View File

@@ -1,26 +1,81 @@
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from toolbox import CatchException, report_execption, write_results_to_file
from toolbox import update_ui
from toolbox import CatchException, report_execption, promote_file_to_downloadzone
from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion, write_history_to_file
import logging
import requests
import time
import random
ENABLE_ALL_VERSION_SEARCH = True
def get_meta_information(url, chatbot, history):
import requests
import arxiv
import difflib
import re
from bs4 import BeautifulSoup
from toolbox import get_conf
from urllib.parse import urlparse
session = requests.session()
proxies, = get_conf('proxies')
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/105.0.0.0 Safari/537.36',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
'Accept-Encoding': 'gzip, deflate, br',
'Accept-Language': 'en-US,en;q=0.9,zh-CN;q=0.8,zh;q=0.7',
'Cache-Control':'max-age=0',
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
'Connection': 'keep-alive'
}
# 发送 GET 请求
response = requests.get(url, proxies=proxies, headers=headers)
try:
session.proxies.update(proxies)
except:
report_execption(chatbot, history,
a=f"获取代理失败 无代理状态下很可能无法访问OpenAI家族的模型及谷歌学术 建议检查USE_PROXY选项是否修改。",
b=f"尝试直接连接")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
session.headers.update(headers)
response = session.get(url)
# 解析网页内容
soup = BeautifulSoup(response.text, "html.parser")
def string_similar(s1, s2):
return difflib.SequenceMatcher(None, s1, s2).quick_ratio()
if ENABLE_ALL_VERSION_SEARCH:
def search_all_version(url):
time.sleep(random.randint(1,5)) # 睡一会防止触发google反爬虫
response = session.get(url)
soup = BeautifulSoup(response.text, "html.parser")
for result in soup.select(".gs_ri"):
try:
url = result.select_one(".gs_rt").a['href']
except:
continue
arxiv_id = extract_arxiv_id(url)
if not arxiv_id:
continue
search = arxiv.Search(
id_list=[arxiv_id],
max_results=1,
sort_by=arxiv.SortCriterion.Relevance,
)
try: paper = next(search.results())
except: paper = None
return paper
return None
def extract_arxiv_id(url):
# 返回给定的url解析出的arxiv_id如url未成功匹配返回None
pattern = r'arxiv.org/abs/([^/]+)'
match = re.search(pattern, url)
if match:
return match.group(1)
else:
return None
profile = []
# 获取所有文章的标题和作者
for result in soup.select(".gs_ri"):
@@ -31,32 +86,45 @@ def get_meta_information(url, chatbot, history):
except:
citation = 'cited by 0'
abstract = result.select_one(".gs_rs").text.strip() # 摘要在 .gs_rs 中的文本,需要清除首尾空格
# 首先在arxiv上搜索获取文章摘要
search = arxiv.Search(
query = title,
max_results = 1,
sort_by = arxiv.SortCriterion.Relevance,
)
try:
paper = next(search.results())
if string_similar(title, paper.title) > 0.90: # same paper
abstract = paper.summary.replace('\n', ' ')
is_paper_in_arxiv = True
else: # different paper
abstract = abstract
is_paper_in_arxiv = False
paper = next(search.results())
except:
try: paper = next(search.results())
except: paper = None
is_match = paper is not None and string_similar(title, paper.title) > 0.90
# 如果在Arxiv上匹配失败检索文章的历史版本的题目
if not is_match and ENABLE_ALL_VERSION_SEARCH:
other_versions_page_url = [tag['href'] for tag in result.select_one('.gs_flb').select('.gs_nph') if 'cluster' in tag['href']]
if len(other_versions_page_url) > 0:
other_versions_page_url = other_versions_page_url[0]
paper = search_all_version('http://' + urlparse(url).netloc + other_versions_page_url)
is_match = paper is not None and string_similar(title, paper.title) > 0.90
if is_match:
# same paper
abstract = paper.summary.replace('\n', ' ')
is_paper_in_arxiv = True
else:
# different paper
abstract = abstract
is_paper_in_arxiv = False
print(title)
print(author)
print(citation)
logging.info('[title]:' + title)
logging.info('[author]:' + author)
logging.info('[citation]:' + citation)
profile.append({
'title':title,
'author':author,
'citation':citation,
'abstract':abstract,
'is_paper_in_arxiv':is_paper_in_arxiv,
'title': title,
'author': author,
'citation': citation,
'abstract': abstract,
'is_paper_in_arxiv': is_paper_in_arxiv,
})
chatbot[-1] = [chatbot[-1][0], title + f'\n\n是否在arxiv中不在arxiv中无法获取完整摘要:{is_paper_in_arxiv}\n\n' + abstract]
@@ -65,6 +133,7 @@ def get_meta_information(url, chatbot, history):
@CatchException
def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
disable_auto_promotion(chatbot=chatbot)
# 基本信息:功能、贡献者
chatbot.append([
"函数插件功能?",
@@ -86,6 +155,9 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
# 清空历史,以免输入溢出
history = []
meta_paper_info_list = yield from get_meta_information(txt, chatbot, history)
if len(meta_paper_info_list) == 0:
yield from update_ui_lastest_msg(lastmsg='获取文献失败可能触发了google反爬虫机制。',chatbot=chatbot, history=history, delay=0)
return
batchsize = 5
for batch in range(math.ceil(len(meta_paper_info_list)/batchsize)):
if len(meta_paper_info_list[:batchsize]) > 0:
@@ -107,6 +179,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
"已经全部完成您可以试试让AI写一个Related Works例如您可以继续输入Write a \"Related Works\" section about \"你搜索的研究领域\" for me."])
msg = '正常'
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面
res = write_results_to_file(history)
chatbot.append(("完成了吗?", res));
path = write_history_to_file(history)
promote_file_to_downloadzone(path, chatbot=chatbot)
chatbot.append(("完成了吗?", path));
yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面

View File

@@ -2,8 +2,8 @@
# @Time : 2023/4/19
# @Author : Spike
# @Descr :
from toolbox import update_ui
from toolbox import CatchException, report_execption, write_results_to_file, get_log_folder
from toolbox import update_ui, get_conf
from toolbox import CatchException
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
@@ -30,14 +30,13 @@ def 猜你想问(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
@CatchException
def 清除缓存(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
chatbot.append(['清除本地缓存数据', '执行中. 删除 gpt_log & private_upload'])
chatbot.append(['清除本地缓存数据', '执行中. 删除数据'])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
import shutil, os
gpt_log_dir = os.path.join(os.path.dirname(__file__), '..', 'gpt_log')
private_upload_dir = os.path.join(os.path.dirname(__file__), '..', 'private_upload')
shutil.rmtree(gpt_log_dir, ignore_errors=True)
shutil.rmtree(private_upload_dir, ignore_errors=True)
PATH_PRIVATE_UPLOAD, PATH_LOGGING = get_conf('PATH_PRIVATE_UPLOAD', 'PATH_LOGGING')
shutil.rmtree(PATH_LOGGING, ignore_errors=True)
shutil.rmtree(PATH_PRIVATE_UPLOAD, ignore_errors=True)
chatbot.append(['清除本地缓存数据', '执行完成'])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面

View File

@@ -1,7 +1,84 @@
#【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
## ===================================================
# docker-compose.yml
## ===================================================
# 1. 请在以下方案中选择任意一种,然后删除其他的方案
# 2. 修改你选择的方案中的environment环境变量详情请见github wiki或者config.py
# 3. 选择一种暴露服务端口的方法,并对相应的配置做出修改:
# 【方法1: 适用于Linux很方便可惜windows不支持】与宿主的网络融合为一体这个是默认配置
# network_mode: "host"
# 【方法2: 适用于所有系统包括Windows和MacOS】端口映射把容器的端口映射到宿主的端口注意您需要先删除network_mode: "host",再追加以下内容)
# ports:
# - "12345:12345" # 注意12345必须与WEB_PORT环境变量相互对应
# 4. 最后`docker-compose up`运行
# 5. 如果希望使用显卡,请关注 LOCAL_MODEL_DEVICE 和 英伟达显卡运行时 选项
## ===================================================
# 1. Please choose one of the following options and delete the others.
# 2. Modify the environment variables in the selected option, see GitHub wiki or config.py for more details.
# 3. Choose a method to expose the server port and make the corresponding configuration changes:
# [Method 1: Suitable for Linux, convenient, but not supported for Windows] Fusion with the host network, this is the default configuration
# network_mode: "host"
# [Method 2: Suitable for all systems including Windows and MacOS] Port mapping, mapping the container port to the host port (note that you need to delete network_mode: "host" first, and then add the following content)
# ports:
# - "12345: 12345" # Note! 12345 must correspond to the WEB_PORT environment variable.
# 4. Finally, run `docker-compose up`.
# 5. If you want to use a graphics card, pay attention to the LOCAL_MODEL_DEVICE and Nvidia GPU runtime options.
## ===================================================
## ===================================================
## 【方案如果不需要运行本地模型仅chatgpt,newbing类远程服务
## 【方案部署项目的全部能力这个是包含cuda和latex的大型镜像。如果您网速慢、硬盘小或没有显卡则不推荐使用这个
## ===================================================
version: '3'
services:
gpt_academic_full_capability:
image: ghcr.io/binary-husky/gpt_academic_with_all_capacity:master
environment:
# 请查阅 `config.py`或者 github wiki 以查看所有的配置信息
API_KEY: ' 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 '
# USE_PROXY: ' True '
# proxies: ' { "http": "http://localhost:10881", "https": "http://localhost:10881", } '
LLM_MODEL: ' gpt-3.5-turbo '
AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "gpt-4", "qianfan", "sparkv2", "spark", "chatglm"] '
BAIDU_CLOUD_API_KEY : ' bTUtwEAveBrQipEowUvDwYWq '
BAIDU_CLOUD_SECRET_KEY : ' jqXtLvXiVw6UNdjliATTS61rllG8Iuni '
XFYUN_APPID: ' 53a8d816 '
XFYUN_API_SECRET: ' MjMxNDQ4NDE4MzM0OSNlNjQ2NTlhMTkx '
XFYUN_API_KEY: ' 95ccdec285364869d17b33e75ee96447 '
ENABLE_AUDIO: ' False '
DEFAULT_WORKER_NUM: ' 20 '
WEB_PORT: ' 12345 '
ADD_WAIFU: ' False '
ALIYUN_APPKEY: ' RxPlZrM88DnAFkZK '
THEME: ' Chuanhu-Small-and-Beautiful '
ALIYUN_ACCESSKEY: ' LTAI5t6BrFUzxRXVGUWnekh1 '
ALIYUN_SECRET: ' eHmI20SVWIwQZxCiTD2bGQVspP9i68 '
# LOCAL_MODEL_DEVICE: ' cuda '
# 加载英伟达显卡运行时
# runtime: nvidia
# deploy:
# resources:
# reservations:
# devices:
# - driver: nvidia
# count: 1
# capabilities: [gpu]
# 【WEB_PORT暴露方法1: 适用于Linux】与宿主的网络融合
network_mode: "host"
# 【WEB_PORT暴露方法2: 适用于所有系统】端口映射
# ports:
# - "12345:12345" # 12345必须与WEB_PORT相互对应
# 启动容器后运行main.py主程序
command: >
bash -c "python3 -u main.py"
## ===================================================
## 【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 +90,7 @@ 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 '

View File

@@ -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
# 此Dockerfile不再维护请前往docs/GithubAction+ChatGLM+Moss
# 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
# 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"]

View File

@@ -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

View File

@@ -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

View File

@@ -0,0 +1,36 @@
# 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
# 准备pip依赖
RUN python3 -m pip install openai numpy arxiv rich
RUN python3 -m pip install colorama Markdown pygments pymupdf
RUN python3 -m pip install python-docx moviepy pdfminer
RUN python3 -m pip install zh_langchain==0.2.1 pypinyin
RUN python3 -m pip install rarfile py7zr
RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
# 下载分支
WORKDIR /gpt
RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
WORKDIR /gpt/gpt_academic
RUN git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llm/moss
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
RUN python3 -m pip install nougat-ocr
# 预热Tiktoken模块
RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()'
# 启动
CMD ["python3", "-u", "main.py"]

View File

@@ -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

View File

@@ -1,15 +1,20 @@
# 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
# 删除文档文件以节约空间
rm -rf /usr/local/texlive/2023/texmf-dist/doc
# 指定路径
WORKDIR /gpt
RUN pip3 install gradio openai numpy arxiv rich
RUN pip3 install openai numpy arxiv rich
RUN pip3 install colorama Markdown pygments pymupdf
RUN pip3 install python-docx pdfminer
RUN pip3 install nougat-ocr
# 装载项目文件
COPY . .

View File

@@ -299,7 +299,6 @@
"地址🚀": "Address 🚀",
"感谢热情的": "Thanks to the enthusiastic",
"开发者们❤️": "Developers ❤️",
"所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log": "All inquiry records will be automatically saved in the local directory ./gpt_log/chat_secrets.log",
"请注意自我隐私保护哦!": "Please pay attention to self-privacy protection!",
"当前模型": "Current model",
"输入区": "Input area",
@@ -323,7 +322,7 @@
"任何文件": "Any file",
"但推荐上传压缩文件": "But it is recommended to upload compressed files",
"更换模型 & SysPrompt & 交互界面布局": "Change model & SysPrompt & interactive interface layout",
"底部输入区": "Bottom input area",
"浮动输入区": "Floating input area",
"输入清除键": "Input clear key",
"插件参数区": "Plugin parameter area",
"显示/隐藏功能区": "Show/hide function area",
@@ -892,7 +891,6 @@
"保存当前对话": "Save current conversation",
"您可以调用“LoadConversationHistoryArchive”还原当下的对话": "You can call 'LoadConversationHistoryArchive' to restore the current conversation",
"警告!被保存的对话历史可以被使用该系统的任何人查阅": "Warning! The saved conversation history can be viewed by anyone using this system",
"gpt_log/**/chatGPT对话历史*.html": "gpt_log/**/chatGPT conversation history *.html",
"正在查找对话历史文件": "Looking for conversation history file",
"html格式": "HTML format",
"找不到任何html文件": "No HTML files found",
@@ -908,7 +906,6 @@
"pip install pywin32 用于doc格式": "pip install pywin32 for doc format",
"仅支持Win平台": "Only supports Win platform",
"打开文件": "Open file",
"private_upload里面的文件名在解压zip后容易出现乱码": "The file name in private_upload is prone to garbled characters after unzipping",
"rar和7z格式正常": "RAR and 7z formats are normal",
"故可以只分析文章内容": "So you can only analyze the content of the article",
"不输入文件名": "Do not enter the file name",
@@ -1364,7 +1361,6 @@
"注意文章中的每一句话都要翻译": "Please translate every sentence in the article",
"一、论文概况": "I. Overview of the paper",
"二、论文翻译": "II. Translation of the paper",
"/gpt_log/总结论文-": "/gpt_log/Summary of the paper-",
"给出输出文件清单": "Provide a list of output files",
"第 0 步": "Step 0",
"切割PDF": "Split PDF",
@@ -1564,7 +1560,6 @@
"广义速度": "Generalized velocity",
"粒子的固有": "Intrinsic of particle",
"一个包含所有切割音频片段文件路径的列表": "A list containing the file paths of all segmented audio clips",
"/gpt_log/翻译-": "Translation log-",
"计算文件总时长和切割点": "Calculate total duration and cutting points of the file",
"总结音频": "Summarize audio",
"作者": "Author",
@@ -2161,5 +2156,498 @@
"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",
"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",
"private_upload里面的文件名在解压zip后容易出现乱码": "The file name inside private_upload is prone to garbled characters after unzipping",
"直接返回报错": "Direct return error",
"临时的上传文件夹位置": "Temporary upload folder location",
"使用latex格式 测试3 写出麦克斯韦方程组": "Write Maxwell's equations using latex format for test 3",
"这是一张图片": "This is an image",
"没有发现任何近期上传的文件": "No recent uploaded files found",
"如url未成功匹配返回None": "Return None if the URL does not match successfully",
"如果有Latex环境": "If there is a Latex environment",
"第一次运行时": "When running for the first time",
"创建工作路径": "Create a working directory",
"向": "To",
"执行中. 删除数据": "Executing. Deleting data",
"CodeInterpreter开源版": "CodeInterpreter open source version",
"建议选择更稳定的接口": "It is recommended to choose a more stable interface",
"现在您点击任意函数插件时": "Now when you click on any function plugin",
"请使用“LatexEnglishCorrection+高亮”插件": "Please use the 'LatexEnglishCorrection+Highlight' plugin",
"安装完成": "Installation completed",
"记得用插件!」": "Remember to use the plugin!",
"结论": "Conclusion",
"无法下载资源": "Unable to download resources",
"首先排除一个one-api没有done数据包的第三方Bug情形": "First exclude a third-party bug where one-api does not have a done data package",
"知识库中添加文件": "Add files to the knowledge base",
"处理重名的章节": "Handling duplicate chapter names",
"先上传文件素材": "Upload file materials first",
"无法从google获取信息": "Unable to retrieve information from Google!",
"展示如下": "Display as follows",
"「把Arxiv论文翻译成中文PDF": "Translate Arxiv papers into Chinese PDF",
"论文我刚刚放到上传区了」": "I just put the paper in the upload area",
"正在下载Gradio主题": "Downloading Gradio themes",
"再运行此插件": "Run this plugin again",
"记录近期文件": "Record recent files",
"粗心检查": "Careful check",
"更多主题": "More themes",
"//huggingface.co/spaces/gradio/theme-gallery 可选": "//huggingface.co/spaces/gradio/theme-gallery optional",
"由 test_on_result_chg": "By test_on_result_chg",
"所有问询记录将自动保存在本地目录./": "All inquiry records will be automatically saved in the local directory ./",
"正在解析论文": "Analyzing the paper",
"逐个文件转移到目标路径": "Move each file to the target path",
"最多重试5次": "Retry up to 5 times",
"日志文件夹的位置": "Location of the log folder",
"我们暂时无法解析此PDF文档": "We are temporarily unable to parse this PDF document",
"文件检索": "File retrieval",
"/**/chatGPT对话历史*.html": "/**/chatGPT conversation history*.html",
"非OpenAI官方接口返回了错误": "Non-OpenAI official interface returned an error",
"如果在Arxiv上匹配失败": "If the match fails on Arxiv",
"文件进入知识库后可长期保存": "Files can be saved for a long time after entering the knowledge base",
"您可以再次重试": "You can try again",
"整理文件集合": "Organize file collection",
"检测到有缺陷的非OpenAI官方接口": "Detected defective non-OpenAI official interface",
"此插件不调用Latex": "This plugin does not call Latex",
"移除过时的旧文件从而节省空间&保护隐私": "Remove outdated old files to save space & protect privacy",
"代码我刚刚打包拖到上传区了」": "I just packed the code and dragged it to the upload area",
"将图像转为灰度图像": "Convert the image to grayscale",
"待排除": "To be excluded",
"请勿修改": "Please do not modify",
"crazy_functions/代码重写为全英文_多线程.py": "crazy_functions/code rewritten to all English_multi-threading.py",
"开发中": "Under development",
"请查阅Gradio主题商店": "Please refer to the Gradio theme store",
"输出消息": "Output message",
"其他情况": "Other situations",
"获取文献失败": "Failed to retrieve literature",
"可以通过再次调用本插件的方式": "You can use this plugin again by calling it",
"保留下半部分": "Keep the lower half",
"排除问题": "Exclude the problem",
"知识库": "Knowledge base",
"ParsePDF失败": "ParsePDF failed",
"向知识库追加更多文档": "Append more documents to the knowledge base",
"此处待注入的知识库名称id": "The knowledge base name ID to be injected here",
"您需要构建知识库后再运行此插件": "You need to build the knowledge base before running this plugin",
"判定是否为公式 | 测试1 写出洛伦兹定律": "Determine whether it is a formula | Test 1 write out the Lorentz law",
"构建知识库后": "After building the knowledge base",
"找不到本地项目或无法处理": "Unable to find local project or unable to process",
"再做一个小修改": "Make another small modification",
"解析整个Matlab项目": "Parse the entire Matlab project",
"需要用GPT提取参数": "Need to extract parameters using GPT",
"文件路径": "File path",
"正在排队": "In queue",
"-=-=-=-=-=-=-=-= 写出第1个文件": "-=-=-=-=-=-=-=-= Write the first file",
"仅翻译后的文本 -=-=-=-=-=-=-=-=": "Translated text only -=-=-=-=-=-=-=-=",
"对话通道": "Conversation channel",
"找不到任何": "Unable to find any",
"正在启动": "Starting",
"开始创建新进程并执行代码! 时间限制": "Start creating a new process and executing the code! Time limit",
"解析Matlab项目": "Parse Matlab project",
"更换UI主题": "Change UI theme",
"⭐ 开始啦 ": "⭐ Let's start!",
"先提取当前英文标题": "First extract the current English title",
"睡一会防止触发google反爬虫": "Sleep for a while to prevent triggering Google anti-crawler",
"测试": "Test",
"-=-=-=-=-=-=-=-= 写出Markdown文件 -=-=-=-=-=-=-=-=": "-=-=-=-=-=-=-=-= Write out Markdown file",
"如果index是1的话": "If the index is 1",
"VoidTerminal已经实现了类似的代码": "VoidTerminal has already implemented similar code",
"等待线程锁": "Waiting for thread lock",
"那么我们默认代理生效": "Then we default to proxy",
"结果是一个有效文件": "The result is a valid file",
"⭐ 检查模块": "⭐ Check module",
"备份一份History作为记录": "Backup a copy of History as a record",
"作者Binary-Husky": "Author Binary-Husky",
"将csv文件转excel表格": "Convert CSV file to Excel table",
"获取文章摘要": "Get article summary",
"次代码生成尝试": "Attempt to generate code",
"如果参数是空的": "If the parameter is empty",
"请配置讯飞星火大模型的XFYUN_APPID": "Please configure XFYUN_APPID for the Xunfei Starfire model",
"-=-=-=-=-=-=-=-= 写出第2个文件": "Write the second file",
"代码生成阶段结束": "Code generation phase completed",
"则进行提醒": "Then remind",
"处理异常": "Handle exception",
"可能触发了google反爬虫机制": "May have triggered Google anti-crawler mechanism",
"AnalyzeAMatlabProject的所有源文件": "All source files of AnalyzeAMatlabProject",
"写入": "Write",
"我们5秒后再试一次...": "Let's try again in 5 seconds...",
"判断一下用户是否错误地通过对话通道进入": "Check if the user entered through the dialogue channel by mistake",
"结果": "Result",
"2. 如果没有文件": "2. If there is no file",
"由 test_on_sentence_end": "By test_on_sentence_end",
"则直接使用first section name": "Then directly use the first section name",
"太懒了": "Too lazy",
"记录当前的大章节标题": "Record the current chapter title",
"然后再次点击该插件! 至于您的文件": "Then click the plugin again! As for your file",
"此次我们的错误追踪是": "This time our error tracking is",
"首先在arxiv上搜索": "First search on arxiv",
"被新插件取代": "Replaced by a new plugin",
"正在处理文件": "Processing file",
"除了连接OpenAI之外": "In addition to connecting OpenAI",
"我们检查一下": "Let's check",
"进度": "Progress",
"处理少数情况下的特殊插件的锁定状态": "Handle the locked state of special plugins in a few cases",
"⭐ 开始执行": "⭐ Start execution",
"正常情况": "Normal situation",
"下个句子中已经说完的部分": "The part that has already been said in the next sentence",
"首次运行需要花费较长时间下载NOUGAT参数": "The first run takes a long time to download NOUGAT parameters",
"使用tex格式公式 测试2 给出柯西不等式": "Use the tex format formula to test 2 and give the Cauchy inequality",
"无法从bing获取信息": "Unable to retrieve information from Bing!",
"秒. 请等待任务完成": "Wait for the task to complete",
"开始干正事": "Start doing real work",
"需要花费较长时间下载NOUGAT参数": "It takes a long time to download NOUGAT parameters",
"然后再次点击该插件": "Then click the plugin again",
"受到bing限制": "Restricted by Bing",
"检索文章的历史版本的题目": "Retrieve the titles of historical versions of the article",
"收尾": "Wrap up",
"给定了task": "Given a task",
"某段话的整个句子": "The whole sentence of a paragraph",
"-=-=-=-=-=-=-=-= 写出HTML文件 -=-=-=-=-=-=-=-=": "-=-=-=-=-=-=-=-= Write out HTML file -=-=-=-=-=-=-=-=",
"当前文件": "Current file",
"请在输入框内填写需求": "Please fill in the requirements in the input box",
"结果是一个字符串": "The result is a string",
"用插件实现」": "Implemented with a plugin",
"⭐ 到最后一步了": "⭐ Reached the final step",
"重新修改当前part的标题": "Modify the title of the current part again",
"请勿点击“提交”按钮或者“基础功能区”按钮": "Do not click the 'Submit' button or the 'Basic Function Area' button",
"正在执行命令": "Executing command",
"检测到**滞留的缓存文档**": "Detected **stuck cache document**",
"第三步": "Step three",
"失败了~ 别担心": "Failed~ Don't worry",
"动态代码解释器": "Dynamic code interpreter",
"开始执行": "Start executing",
"不给定task": "No task given",
"正在加载NOUGAT...": "Loading NOUGAT...",
"精准翻译PDF文档": "Accurate translation of PDF documents",
"时间限制TIME_LIMIT": "Time limit TIME_LIMIT",
"翻译前后混合 -=-=-=-=-=-=-=-=": "Mixed translation before and after -=-=-=-=-=-=-=-=",
"搞定代码生成": "Code generation is done",
"插件通道": "Plugin channel",
"智能体": "Intelligent agent",
"切换界面明暗 ☀": "Switch interface brightness ☀",
"交换图像的蓝色通道和红色通道": "Swap blue channel and red channel of the image",
"作为函数参数": "As a function parameter",
"先挑选偶数序列号": "First select even serial numbers",
"仅供测试": "For testing only",
"执行成功了": "Execution succeeded",
"开始逐个文件进行处理": "Start processing files one by one",
"当前文件处理列表": "Current file processing list",
"执行失败了": "Execution failed",
"请及时处理": "Please handle it in time",
"源文件": "Source file",
"裁剪图像": "Crop image",
"插件动态生成插件": "Dynamic generation of plugins",
"正在验证上述代码的有效性": "Validating the above code",
"⭐ = 关键步骤": "⭐ = Key step",
"!= 0 代表“提交”键对话通道": "!= 0 represents the 'Submit' key dialogue channel",
"解析python源代码项目": "Parsing Python source code project",
"请检查PDF是否损坏": "Please check if the PDF is damaged",
"插件动态生成": "Dynamic generation of plugins",
"⭐ 分离代码块": "⭐ Separating code blocks",
"已经被记忆": "Already memorized",
"默认用英文的": "Default to English",
"错误追踪": "Error tracking",
"对话|编程|学术|智能体": "Dialogue|Programming|Academic|Intelligent agent",
"请检查": "Please check",
"检测到被滞留的缓存文档": "Detected cached documents being left behind",
"还有哪些场合允许使用代理": "What other occasions allow the use of proxies",
"1. 如果有文件": "1. If there is a file",
"执行开始": "Execution starts",
"代码生成结束": "Code generation ends",
"请及时点击“**保存当前对话**”获取所有滞留文档": "Please click '**Save Current Dialogue**' in time to obtain all cached documents",
"需点击“**函数插件区**”按钮进行处理": "Click the '**Function Plugin Area**' button for processing",
"此函数已经弃用": "This function has been deprecated",
"以后再写": "Write it later",
"返回给定的url解析出的arxiv_id": "Return the arxiv_id parsed from the given URL",
"⭐ 文件上传区是否有东西": "⭐ Is there anything in the file upload area",
"Nougat解析论文失败": "Nougat failed to parse the paper",
"本源代码中": "In this source code",
"或者基础功能通道": "Or the basic function channel",
"使用zip压缩格式": "Using zip compression format",
"受到google限制": "Restricted by Google",
"如果是": "If it is",
"不用担心": "don't worry"
}

View File

@@ -301,7 +301,6 @@
"缺少的依赖": "不足している依存関係",
"紫色": "紫色",
"唤起高级参数输入区": "高度なパラメータ入力エリアを呼び出す",
"所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log": "すべての問い合わせ記録は自動的にローカルディレクトリ./gpt_log/chat_secrets.logに保存されます",
"则换行符更有可能表示段落分隔": "したがって、改行記号は段落の区切りを表す可能性がより高いです",
"4、引用数量": "4、引用数量",
"中转网址预览": "中継ウェブサイトのプレビュー",
@@ -448,7 +447,6 @@
"表示函数是否成功执行": "関数が正常に実行されたかどうかを示す",
"一般原样传递下去就行": "通常はそのまま渡すだけでよい",
"琥珀色": "琥珀色",
"gpt_log/**/chatGPT对话历史*.html": "gpt_log/**/chatGPT対話履歴*.html",
"jittorllms 没有 sys_prompt 接口": "jittorllmsにはsys_promptインターフェースがありません",
"清除": "クリア",
"小于正文的": "本文より小さい",
@@ -1009,7 +1007,6 @@
"第一部分": "第1部分",
"的分析如下": "の分析は以下の通りです",
"解决一个mdx_math的bug": "mdx_mathのバグを解決する",
"底部输入区": "下部の入力エリア",
"函数插件输入输出接驳区": "関数プラグインの入出力接続エリア",
"打开浏览器": "ブラウザを開く",
"免费用户填3": "無料ユーザーは3を入力してください",
@@ -1234,7 +1231,6 @@
"找不到任何前端相关文件": "No frontend-related files can be found",
"Not enough point. API2D账户点数不足": "Not enough points. API2D account points are insufficient",
"当前版本": "Current version",
"/gpt_log/总结论文-": "/gpt_log/Summary paper-",
"1. 临时解决方案": "1. Temporary solution",
"第8步": "Step 8",
"历史": "History",

View File

@@ -83,5 +83,14 @@
"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",
"批量翻译PDF文档_NOUGAT": "BatchTranslatePDFDocuments_NOUGAT",
"解析PDF_基于NOUGAT": "ParsePDF_NOUGAT",
"解析一个Matlab项目": "AnalyzeAMatlabProject",
"函数动态生成": "DynamicFunctionGeneration"
}

View File

@@ -314,7 +314,6 @@
"请用markdown格式输出": "請用 Markdown 格式輸出",
"模仿ChatPDF": "模仿 ChatPDF",
"等待多久判定为超时": "等待多久判定為超時",
"/gpt_log/总结论文-": "/gpt_log/總結論文-",
"请结合互联网信息回答以下问题": "請結合互聯網信息回答以下問題",
"IP查询频率受限": "IP查詢頻率受限",
"高级参数输入区的显示提示": "高級參數輸入區的顯示提示",
@@ -347,7 +346,6 @@
"情况会好转": "情況會好轉",
"超过512个": "超過512個",
"多线": "多線",
"底部输入区": "底部輸入區",
"合并小写字母开头的段落块并替换为空格": "合併小寫字母開頭的段落塊並替換為空格",
"暗色主题": "暗色主題",
"提高限制请查询": "提高限制請查詢",
@@ -511,7 +509,6 @@
"將生成的報告自動投射到文件上傳區": "將生成的報告自動上傳到文件區",
"函數插件作者": "函數插件作者",
"將要匹配的模式": "將要匹配的模式",
"所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log": "所有詢問記錄將自動保存在本地目錄./gpt_log/chat_secrets.log",
"正在分析一个项目的源代码": "正在分析一個專案的源代碼",
"使每个段落之间有两个换行符分隔": "使每個段落之間有兩個換行符分隔",
"并在被装饰的函数上执行": "並在被裝飾的函數上執行",
@@ -1059,7 +1056,6 @@
"重试中": "重試中",
"月": "月份",
"localhost意思是代理软件安装在本机上": "localhost意思是代理軟體安裝在本機上",
"gpt_log/**/chatGPT对话历史*.html": "gpt_log/**/chatGPT對話歷史*.html",
"的长度必须小于 2500 个 Token": "長度必須小於 2500 個 Token",
"抽取可用的api-key": "提取可用的api-key",
"增强报告的可读性": "增強報告的可讀性",

View File

@@ -107,6 +107,12 @@ AZURE_API_KEY = "填入azure openai api的密钥"
AZURE_API_VERSION = "2023-05-15" # 默认使用 2023-05-15 版本,无需修改
AZURE_ENGINE = "填入部署名" # 见上述图片
# 例如
API_KEY = '6424e9d19e674092815cea1cb35e67a5'
AZURE_ENDPOINT = 'https://rhtjjjjjj.openai.azure.com/'
AZURE_ENGINE = 'qqwe'
LLM_MODEL = "azure-gpt-3.5" # 可选 ↓↓↓
```

278
main.py
View File

@@ -1,32 +1,46 @@
import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
import pickle
import codecs
import base64
def main():
import gradio as gr
if gr.__version__ not in ['3.28.3','3.32.2']: assert False, "需要特殊依赖,请务必用 pip install -r requirements.txt 指令安装依赖详情信息见requirements.txt"
if gr.__version__ not in ['3.32.6']:
raise ModuleNotFoundError("使用项目内置Gradio获取最优体验! 请运行 `pip install -r requirements.txt` 指令安装内置Gradio及其他依赖, 详情信息见requirements.txt.")
from request_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 = 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')
ENABLE_AUDIO, AUTO_CLEAR_TXT, PATH_LOGGING, AVAIL_THEMES, THEME = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'PATH_LOGGING', 'AVAIL_THEMES', 'THEME')
DARK_MODE, NUM_CUSTOM_BASIC_BTN, SSL_KEYFILE, SSL_CERTFILE = get_conf('DARK_MODE', 'NUM_CUSTOM_BASIC_BTN', 'SSL_KEYFILE', 'SSL_CERTFILE')
# 如果WEB_PORT是-1, 则随机选取WEB端口
PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
from check_proxy import get_current_version
from themes.theme import adjust_theme, advanced_css, theme_declaration
from themes.theme import adjust_theme, advanced_css, theme_declaration, load_dynamic_theme
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/gpt_academic)"
description += "感谢热情的[开发者们❤️](https://github.com/binary-husky/gpt_academic/graphs/contributors)"
description = "Github源代码开源和更新[地址🚀](https://github.com/binary-husky/gpt_academic), "
description += "感谢热情的[开发者们❤️](https://github.com/binary-husky/gpt_academic/graphs/contributors)."
description += "</br></br>常见问题请查阅[项目Wiki](https://github.com/binary-husky/gpt_academic/wiki), "
description += "如遇到Bug请前往[Bug反馈](https://github.com/binary-husky/gpt_academic/issues)."
description += "</br></br>普通对话使用说明: 1. 输入问题; 2. 点击提交"
description += "</br></br>基础功能区使用说明: 1. 输入文本; 2. 点击任意基础功能区按钮"
description += "</br></br>函数插件区使用说明: 1. 输入路径/问题, 或者上传文件; 2. 点击任意函数插件区按钮"
description += "</br></br>虚空终端使用说明: 点击虚空终端, 然后根据提示输入指令, 再次点击虚空终端"
description += "</br></br>如何保存对话: 点击保存当前的对话按钮"
description += "</br></br>如何语音对话: 请阅读Wiki"
# 问询记录, python 版本建议3.9+(越新越好)
import logging, uuid
os.makedirs("gpt_log", exist_ok=True)
try:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, encoding="utf-8", format="%(asctime)s %(levelname)-8s %(message)s", datefmt="%Y-%m-%d %H:%M:%S")
except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, format="%(asctime)s %(levelname)-8s %(message)s", datefmt="%Y-%m-%d %H:%M:%S")
os.makedirs(PATH_LOGGING, exist_ok=True)
try:logging.basicConfig(filename=f"{PATH_LOGGING}/chat_secrets.log", level=logging.INFO, encoding="utf-8", format="%(asctime)s %(levelname)-8s %(message)s", datefmt="%Y-%m-%d %H:%M:%S")
except:logging.basicConfig(filename=f"{PATH_LOGGING}/chat_secrets.log", level=logging.INFO, format="%(asctime)s %(levelname)-8s %(message)s", datefmt="%Y-%m-%d %H:%M:%S")
# Disable logging output from the 'httpx' logger
logging.getLogger("httpx").setLevel(logging.WARNING)
print("所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log, 请注意自我隐私保护哦!")
print(f"所有问询记录将自动保存在本地目录./{PATH_LOGGING}/chat_secrets.log, 请注意自我隐私保护哦!")
# 一些普通功能模块
from core_functional import get_core_functions
@@ -57,8 +71,11 @@ def main():
CHATBOT_HEIGHT /= 2
cancel_handles = []
customize_btns = {}
predefined_btns = {}
with gr.Blocks(title="GPT 学术优化", theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
gr.HTML(title_html)
secret_css, dark_mode, persistent_cookie = gr.Textbox(visible=False), gr.Textbox(DARK_MODE, visible=False), gr.Textbox(visible=False)
cookies = gr.State(load_chat_cookies())
with gr_L1():
with gr_L2(scale=2, elem_id="gpt-chat"):
@@ -70,11 +87,11 @@ def main():
with gr.Row():
txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
with gr.Row():
submitBtn = gr.Button("提交", variant="primary")
submitBtn = gr.Button("提交", elem_id="elem_submit", variant="primary")
with gr.Row():
resetBtn = gr.Button("重置", variant="secondary"); resetBtn.style(size="sm")
stopBtn = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
clearBtn = gr.Button("清除", variant="secondary", visible=False); clearBtn.style(size="sm")
resetBtn = gr.Button("重置", elem_id="elem_reset", variant="secondary"); resetBtn.style(size="sm")
stopBtn = gr.Button("停止", elem_id="elem_stop", variant="secondary"); stopBtn.style(size="sm")
clearBtn = gr.Button("清除", elem_id="elem_clear", variant="secondary", visible=False); clearBtn.style(size="sm")
if ENABLE_AUDIO:
with gr.Row():
audio_mic = gr.Audio(source="microphone", type="numpy", streaming=True, show_label=False).style(container=False)
@@ -82,11 +99,16 @@ def main():
status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}", elem_id="state-panel")
with gr.Accordion("基础功能区", open=True, elem_id="basic-panel") as area_basic_fn:
with gr.Row():
for k in range(NUM_CUSTOM_BASIC_BTN):
customize_btn = gr.Button("自定义按钮" + str(k+1), visible=False, variant="secondary", info_str=f'基础功能区: 自定义按钮')
customize_btn.style(size="sm")
customize_btns.update({"自定义按钮" + str(k+1): customize_btn})
for k in functional:
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"] = gr.Button(k, variant=variant, info_str=f'基础功能区: {k}')
functional[k]["Button"].style(size="sm")
predefined_btns.update({k: functional[k]["Button"]})
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)")
@@ -98,7 +120,9 @@ def main():
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")
info = plugins[k].get("Info", k)
plugin['Button'] = plugins[k]['Button'] = gr.Button(k, variant=variant,
visible=visible, info_str=f'函数插件区: {info}').style(size="sm")
with gr.Row():
with gr.Accordion("更多函数插件", open=True):
dropdown_fn_list = []
@@ -115,42 +139,148 @@ def main():
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, 推荐上传压缩文件(zip, tar)", file_count="multiple")
with gr.Accordion("更换模型 & SysPrompt & 交互界面布局", open=(LAYOUT == "TOP-DOWN"), elem_id="interact-panel"):
system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
file_upload = gr.Files(label="任何文件, 推荐上传压缩文件(zip, tar)", file_count="multiple", elem_id="elem_upload")
with gr.Floating(init_x="0%", init_y="0%", visible=True, width=None, drag="forbidden"):
with gr.Row():
with gr.Tab("上传文件", elem_id="interact-panel"):
gr.Markdown("请上传本地文件/压缩包供“函数插件区”功能调用。请注意: 上传文件后会自动把输入区修改为相应路径。")
file_upload_2 = gr.Files(label="任何文件, 推荐上传压缩文件(zip, tar)", file_count="multiple")
with gr.Tab("更换模型 & Prompt", elem_id="interact-panel"):
md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False)
top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
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)
max_length_sl = gr.Slider(minimum=256, maximum=1024*32, value=4096, step=128, interactive=True, label="Local LLM MaxLength",)
system_prompt = gr.Textbox(show_label=True, lines=2, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
with gr.Tab("界面外观", elem_id="interact-panel"):
theme_dropdown = gr.Dropdown(AVAIL_THEMES, value=THEME, label="更换UI主题").style(container=False)
checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "浮动输入区", "输入清除键", "插件参数区"],
value=["基础功能区", "函数插件区"], label="显示/隐藏功能区", elem_id='cbs').style(container=False)
checkboxes_2 = gr.CheckboxGroup(["自定义菜单"],
value=[], label="显示/隐藏自定义菜单", elem_id='cbs').style(container=False)
dark_mode_btn = gr.Button("切换界面明暗 ☀", variant="secondary").style(size="sm")
dark_mode_btn.click(None, None, None, _js="""() => {
if (document.querySelectorAll('.dark').length) {
document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark'));
} else {
document.querySelector('body').classList.add('dark');
}
}""",
)
with gr.Tab("帮助", elem_id="interact-panel"):
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():
txt2 = gr.Textbox(show_label=False, placeholder="Input question here.", label="输入区2").style(container=False)
with gr.Row():
submitBtn2 = gr.Button("提交", variant="primary")
with gr.Row():
with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_input_secondary:
with gr.Accordion("浮动输入区", open=True, elem_id="input-panel2"):
with gr.Row() as row:
row.style(equal_height=True)
with gr.Column(scale=10):
txt2 = gr.Textbox(show_label=False, placeholder="Input question here.", lines=8, label="输入区2").style(container=False)
with gr.Column(scale=1, min_width=40):
submitBtn2 = gr.Button("提交", variant="primary"); submitBtn2.style(size="sm")
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")
def to_cookie_str(d):
# Pickle the dictionary and encode it as a string
pickled_dict = pickle.dumps(d)
cookie_value = base64.b64encode(pickled_dict).decode('utf-8')
return cookie_value
def from_cookie_str(c):
# Decode the base64-encoded string and unpickle it into a dictionary
pickled_dict = base64.b64decode(c.encode('utf-8'))
return pickle.loads(pickled_dict)
with gr.Floating(init_x="20%", init_y="50%", visible=False, width="40%", drag="top") as area_customize:
with gr.Accordion("自定义菜单", open=True, elem_id="edit-panel"):
with gr.Row() as row:
with gr.Column(scale=10):
AVAIL_BTN = [btn for btn in customize_btns.keys()] + [k for k in functional]
basic_btn_dropdown = gr.Dropdown(AVAIL_BTN, value="自定义按钮1", label="选择一个需要自定义基础功能区按钮").style(container=False)
basic_fn_title = gr.Textbox(show_label=False, placeholder="输入新按钮名称", lines=1).style(container=False)
basic_fn_prefix = gr.Textbox(show_label=False, placeholder="输入新提示前缀", lines=4).style(container=False)
basic_fn_suffix = gr.Textbox(show_label=False, placeholder="输入新提示后缀", lines=4).style(container=False)
with gr.Column(scale=1, min_width=70):
basic_fn_confirm = gr.Button("确认并保存", variant="primary"); basic_fn_confirm.style(size="sm")
basic_fn_load = gr.Button("加载已保存", variant="primary"); basic_fn_load.style(size="sm")
def assign_btn(persistent_cookie_, cookies_, basic_btn_dropdown_, basic_fn_title, basic_fn_prefix, basic_fn_suffix):
ret = {}
customize_fn_overwrite_ = cookies_['customize_fn_overwrite']
customize_fn_overwrite_.update({
basic_btn_dropdown_:
{
"Title":basic_fn_title,
"Prefix":basic_fn_prefix,
"Suffix":basic_fn_suffix,
}
}
)
cookies_.update(customize_fn_overwrite_)
if basic_btn_dropdown_ in customize_btns:
ret.update({customize_btns[basic_btn_dropdown_]: gr.update(visible=True, value=basic_fn_title)})
else:
ret.update({predefined_btns[basic_btn_dropdown_]: gr.update(visible=True, value=basic_fn_title)})
ret.update({cookies: cookies_})
try: persistent_cookie_ = from_cookie_str(persistent_cookie_) # persistent cookie to dict
except: persistent_cookie_ = {}
persistent_cookie_["custom_bnt"] = customize_fn_overwrite_ # dict update new value
persistent_cookie_ = to_cookie_str(persistent_cookie_) # persistent cookie to dict
ret.update({persistent_cookie: persistent_cookie_}) # write persistent cookie
return ret
def reflesh_btn(persistent_cookie_, cookies_):
ret = {}
for k in customize_btns:
ret.update({customize_btns[k]: gr.update(visible=False, value="")})
try: persistent_cookie_ = from_cookie_str(persistent_cookie_) # persistent cookie to dict
except: return ret
customize_fn_overwrite_ = persistent_cookie_.get("custom_bnt", {})
cookies_['customize_fn_overwrite'] = customize_fn_overwrite_
ret.update({cookies: cookies_})
for k,v in persistent_cookie_["custom_bnt"].items():
if v['Title'] == "": continue
if k in customize_btns: ret.update({customize_btns[k]: gr.update(visible=True, value=v['Title'])})
else: ret.update({predefined_btns[k]: gr.update(visible=True, value=v['Title'])})
return ret
basic_fn_load.click(reflesh_btn, [persistent_cookie, cookies],[cookies, *customize_btns.values(), *predefined_btns.values()])
h = basic_fn_confirm.click(assign_btn, [persistent_cookie, cookies, basic_btn_dropdown, basic_fn_title, basic_fn_prefix, basic_fn_suffix],
[persistent_cookie, cookies, *customize_btns.values(), *predefined_btns.values()])
h.then(None, [persistent_cookie], None, _js="""(persistent_cookie)=>{setCookie("persistent_cookie", persistent_cookie, 5);}""") # save persistent cookie
# 功能区显示开关与功能区的互动
def fn_area_visibility(a):
ret = {}
ret.update({area_basic_fn: gr.update(visible=("基础功能区" in a))})
ret.update({area_crazy_fn: gr.update(visible=("函数插件区" in a))})
ret.update({area_input_primary: gr.update(visible=("底部输入区" not in a))})
ret.update({area_input_secondary: gr.update(visible=("底部输入区" in a))})
ret.update({area_input_primary: gr.update(visible=("浮动输入区" not in a))})
ret.update({area_input_secondary: gr.update(visible=("浮动输入区" in a))})
ret.update({clearBtn: gr.update(visible=("输入清除键" in a))})
ret.update({clearBtn2: gr.update(visible=("输入清除键" in a))})
ret.update({plugin_advanced_arg: gr.update(visible=("插件参数区" in a))})
if "底部输入区" in a: ret.update({txt: gr.update(value="")})
if "浮动输入区" in a: ret.update({txt: gr.update(value="")})
return ret
checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn, area_input_primary, area_input_secondary, txt, txt2, clearBtn, clearBtn2, plugin_advanced_arg] )
# 功能区显示开关与功能区的互动
def fn_area_visibility_2(a):
ret = {}
ret.update({area_customize: gr.update(visible=("自定义菜单" in a))})
return ret
checkboxes_2.select(fn_area_visibility_2, [checkboxes_2], [area_customize] )
# 整理反复出现的控件句柄组合
input_combo = [cookies, max_length_sl, md_dropdown, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg]
output_combo = [cookies, chatbot, history, status]
predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=input_combo, outputs=output_combo)
predict_args = dict(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True)], outputs=output_combo)
# 提交按钮、重置按钮
cancel_handles.append(txt.submit(**predict_args))
cancel_handles.append(txt2.submit(**predict_args))
@@ -170,32 +300,65 @@ def main():
if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
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)
for btn in customize_btns.values():
click_handle = btn.click(fn=ArgsGeneralWrapper(predict), inputs=[*input_combo, gr.State(True), gr.State(btn.value)], outputs=output_combo)
cancel_handles.append(click_handle)
# 文件上传区接收文件后与chatbot的互动
file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies])
file_upload_2.upload(on_file_uploaded, [file_upload_2, chatbot, txt, txt2, checkboxes, cookies], [chatbot, txt, txt2, cookies])
# 函数插件-固定按钮区
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 = plugins[k]["Button"].click(ArgsGeneralWrapper(plugins[k]["Function"]), [*input_combo], 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 = plugins[k]["Color"] if "Color" in plugins[k] else "secondary"
ret = {switchy_bt: gr.update(value=k, variant=variant)}
info = plugins[k].get("Info", k)
ret = {switchy_bt: gr.update(value=k, variant=variant, info_str=f'函数插件区: {info}')}
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
dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt, plugin_advanced_arg] )
def on_md_dropdown_changed(k):
return {chatbot: gr.update(label="当前模型:"+k)}
md_dropdown.select(on_md_dropdown_changed, [md_dropdown], [chatbot] )
def on_theme_dropdown_changed(theme, secret_css):
adjust_theme, css_part1, _, adjust_dynamic_theme = load_dynamic_theme(theme)
if adjust_dynamic_theme:
css_part2 = adjust_dynamic_theme._get_theme_css()
else:
css_part2 = adjust_theme()._get_theme_css()
return css_part2 + css_part1
theme_handle = theme_dropdown.select(on_theme_dropdown_changed, [theme_dropdown, secret_css], [secret_css])
theme_handle.then(
None,
[secret_css],
None,
_js="""(css) => {
var existingStyles = document.querySelectorAll("style[data-loaded-css]");
for (var i = 0; i < existingStyles.length; i++) {
var style = existingStyles[i];
style.parentNode.removeChild(style);
}
var styleElement = document.createElement('style');
styleElement.setAttribute('data-loaded-css', css);
styleElement.innerHTML = css;
document.head.appendChild(styleElement);
}
"""
)
# 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(plugins[k]["Function"])(request, *args, **kwargs)
click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
click_handle = switchy_bt.click(route,[switchy_bt, *input_combo], 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
@@ -226,26 +389,47 @@ def main():
cookies.update({'uuid': uuid.uuid4()})
return cookies
demo.load(init_cookie, inputs=[cookies, chatbot], outputs=[cookies])
demo.load(lambda: 0, inputs=None, outputs=None, _js='()=>{ChatBotHeight();}')
darkmode_js = """(dark) => {
dark = dark == "True";
if (document.querySelectorAll('.dark').length) {
if (!dark){
document.querySelectorAll('.dark').forEach(el => el.classList.remove('dark'));
}
} else {
if (dark){
document.querySelector('body').classList.add('dark');
}
}
}"""
load_cookie_js = """(persistent_cookie) => {
return getCookie("persistent_cookie");
}"""
demo.load(None, inputs=None, outputs=[persistent_cookie], _js=load_cookie_js)
demo.load(None, inputs=[dark_mode], outputs=None, _js=darkmode_js) # 配置暗色主题或亮色主题
demo.load(None, inputs=[gr.Textbox(LAYOUT, visible=False)], outputs=None, _js='(LAYOUT)=>{GptAcademicJavaScriptInit(LAYOUT);}')
# gradio的inbrowser触发不太稳定回滚代码到原始的浏览器打开函数
def auto_opentab_delay():
def run_delayed_tasks():
import threading, webbrowser, time
print(f"如果浏览器没有自动打开请复制并转到以下URL")
print(f"\t(亮色主题): http://localhost:{PORT}")
print(f"\t(暗色主题): http://localhost:{PORT}/?__theme=dark")
def open():
time.sleep(2) # 打开浏览器
DARK_MODE, = get_conf('DARK_MODE')
if DARK_MODE: webbrowser.open_new_tab(f"http://localhost:{PORT}/?__theme=dark")
else: webbrowser.open_new_tab(f"http://localhost:{PORT}")
threading.Thread(target=open, name="open-browser", daemon=True).start()
threading.Thread(target=auto_update, name="self-upgrade", daemon=True).start()
threading.Thread(target=warm_up_modules, name="warm-up", daemon=True).start()
if DARK_MODE: print(f"\t「暗色主题已启用(支持动态切换主题): http://localhost:{PORT}")
else: print(f"\t「亮色主题已启用(支持动态切换主题): http://localhost:{PORT}")
auto_opentab_delay()
def auto_updates(): time.sleep(0); auto_update()
def open_browser(): time.sleep(2); webbrowser.open_new_tab(f"http://localhost:{PORT}")
def warm_up_mods(): time.sleep(4); warm_up_modules()
threading.Thread(target=auto_updates, name="self-upgrade", daemon=True).start() # 查看自动更新
threading.Thread(target=open_browser, name="open-browser", daemon=True).start() # 打开浏览器页面
threading.Thread(target=warm_up_mods, name="warm-up", daemon=True).start() # 预热tiktoken模块
run_delayed_tasks()
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
quiet=True,
server_name="0.0.0.0",
ssl_keyfile=None if SSL_KEYFILE == "" else SSL_KEYFILE,
ssl_certfile=None if SSL_CERTFILE == "" else SSL_CERTFILE,
ssl_verify=False,
server_port=PORT,
favicon_path="docs/logo.png",
auth=AUTHENTICATION if len(AUTHENTICATION) != 0 else None,

View File

@@ -33,9 +33,11 @@ import functools
import re
import pickle
import time
from toolbox import get_conf
CACHE_FOLDER = "gpt_log"
blacklist = ['multi-language', 'gpt_log', '.git', 'private_upload', 'multi_language.py', 'build', '.github', '.vscode', '__pycache__', 'venv']
CACHE_FOLDER, = get_conf('PATH_LOGGING')
blacklist = ['multi-language', CACHE_FOLDER, '.git', 'private_upload', 'multi_language.py', 'build', '.github', '.vscode', '__pycache__', 'venv']
# LANG = "TraditionalChinese"
# TransPrompt = f"Replace each json value `#` with translated results in Traditional Chinese, e.g., \"原始文本\":\"翻譯後文字\". Keep Json format. Do not answer #."
@@ -478,6 +480,8 @@ 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])))
# ===============================================

View File

@@ -52,6 +52,7 @@ API_URL_REDIRECT, AZURE_ENDPOINT, AZURE_ENGINE = get_conf("API_URL_REDIRECT", "A
openai_endpoint = "https://api.openai.com/v1/chat/completions"
api2d_endpoint = "https://openai.api2d.net/v1/chat/completions"
newbing_endpoint = "wss://sydney.bing.com/sydney/ChatHub"
if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/'
azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
# 兼容旧版的配置
try:
@@ -125,6 +126,24 @@ model_info = {
"token_cnt": get_token_num_gpt4,
},
"gpt-4-32k": {
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
"endpoint": openai_endpoint,
"max_token": 32768,
"tokenizer": tokenizer_gpt4,
"token_cnt": get_token_num_gpt4,
},
"gpt-3.5-random": {
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
"endpoint": openai_endpoint,
"max_token": 4096,
"tokenizer": tokenizer_gpt4,
"token_cnt": get_token_num_gpt4,
},
# azure openai
"azure-gpt-3.5":{
"fn_with_ui": chatgpt_ui,
@@ -135,6 +154,15 @@ model_info = {
"token_cnt": get_token_num_gpt35,
},
"azure-gpt-4":{
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
"endpoint": azure_endpoint,
"max_token": 8192,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
# api_2d
"api2d-gpt-3.5-turbo": {
"fn_with_ui": chatgpt_ui,

View File

@@ -3,7 +3,7 @@ from transformers import AutoModel, AutoTokenizer
import time
import threading
import importlib
from toolbox import update_ui, get_conf
from toolbox import update_ui, get_conf, ProxyNetworkActivate
from multiprocessing import Process, Pipe
load_message = "ChatGLM尚未加载加载需要一段时间。注意取决于`config.py`的配置ChatGLM消耗大量的内存CPU或显存GPU也许会导致低配计算机卡死 ……"
@@ -48,16 +48,17 @@ class GetGLMHandle(Process):
while True:
try:
if self.chatglm_model is None:
self.chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True)
if device=='cpu':
self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).float()
with ProxyNetworkActivate('Download_LLM'):
if self.chatglm_model is None:
self.chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True)
if device=='cpu':
self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).float()
else:
self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).half().cuda()
self.chatglm_model = self.chatglm_model.eval()
break
else:
self.chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).half().cuda()
self.chatglm_model = self.chatglm_model.eval()
break
else:
break
break
except:
retry += 1
if retry > 3:

View File

@@ -18,10 +18,11 @@ import logging
import traceback
import requests
import importlib
import random
# config_private.py放自己的秘密如API和代理网址
# 读取时首先看是否存在私密的config_private配置文件不受git管控如果有则覆盖原config文件
from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc
from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder
proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG = \
get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG')
@@ -39,6 +40,21 @@ def get_full_error(chunk, stream_response):
break
return chunk
def decode_chunk(chunk):
# 提前读取一些信息 (用于判断异常)
chunk_decoded = chunk.decode()
chunkjson = None
has_choices = False
has_content = False
has_role = False
try:
chunkjson = json.loads(chunk_decoded[6:])
has_choices = 'choices' in chunkjson
if has_choices: has_content = "content" in chunkjson['choices'][0]["delta"]
if has_choices: has_role = "role" in chunkjson['choices'][0]["delta"]
except:
pass
return chunk_decoded, chunkjson, has_choices, has_content, has_role
def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
"""
@@ -72,6 +88,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
stream_response = response.iter_lines()
result = ''
json_data = None
while True:
try: chunk = next(stream_response).decode()
except StopIteration:
@@ -95,15 +112,16 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
if not console_slience: print(delta["content"], end='')
if observe_window is not None:
# 观测窗,把已经获取的数据显示出去
if len(observe_window) >= 1: observe_window[0] += delta["content"]
if len(observe_window) >= 1:
observe_window[0] += delta["content"]
# 看门狗,如果超过期限没有喂狗,则终止
if len(observe_window) >= 2:
if (time.time()-observe_window[1]) > watch_dog_patience:
raise RuntimeError("用户取消了程序。")
else: raise RuntimeError("意外Json结构"+delta)
if json_data['finish_reason'] == 'content_filter':
if json_data and json_data['finish_reason'] == 'content_filter':
raise RuntimeError("由于提问含不合规内容被Azure过滤。")
if json_data['finish_reason'] == 'length':
if json_data and json_data['finish_reason'] == 'length':
raise ConnectionAbortedError("正常结束但显示Token不足导致输出不完整请削减单次输入的文本量。")
return result
@@ -128,6 +146,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
yield from update_ui(chatbot=chatbot, history=history, msg="缺少api_key") # 刷新界面
return
user_input = inputs
if additional_fn is not None:
from core_functional import handle_core_functionality
inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
@@ -138,8 +157,8 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
# check mis-behavior
if raw_input.startswith('private_upload/') and len(raw_input) == 34:
chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误!当您上传文档之后,需点击“函数插件区”按钮进行处理,而不是点击“提交”按钮。")
if is_the_upload_folder(user_input):
chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误!当您上传文档之后,需点击“**函数插件区**”按钮进行处理,请勿点击“提交”按钮或者“基础功能区”按钮")
yield from update_ui(chatbot=chatbot, history=history, msg="正常") # 刷新界面
time.sleep(2)
@@ -179,11 +198,18 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
# 非OpenAI官方接口的出现这样的报错OpenAI和API2D不会走这里
chunk_decoded = chunk.decode()
error_msg = chunk_decoded
# 首先排除一个one-api没有done数据包的第三方Bug情形
if len(gpt_replying_buffer.strip()) > 0 and len(error_msg) == 0:
yield from update_ui(chatbot=chatbot, history=history, msg="检测到有缺陷的非OpenAI官方接口建议选择更稳定的接口。")
break
# 其他情况,直接返回报错
chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
yield from update_ui(chatbot=chatbot, history=history, msg="非Openai官方接口返回了错误:" + chunk.decode()) # 刷新界面
yield from update_ui(chatbot=chatbot, history=history, msg="非OpenAI官方接口返回了错误:" + chunk.decode()) # 刷新界面
return
chunk_decoded = chunk.decode()
# 提前读取一些信息 (用于判断异常)
chunk_decoded, chunkjson, has_choices, has_content, has_role = decode_chunk(chunk)
if is_head_of_the_stream and (r'"object":"error"' not in chunk_decoded) and (r"content" not in chunk_decoded):
# 数据流的第一帧不携带content
is_head_of_the_stream = False; continue
@@ -191,15 +217,23 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
if chunk:
try:
# 前者是API2D的结束条件后者是OPENAI的结束条件
if ('data: [DONE]' in chunk_decoded) or (len(json.loads(chunk_decoded[6:])['choices'][0]["delta"]) == 0):
if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
# 判定为数据流的结束gpt_replying_buffer也写完了
logging.info(f'[response] {gpt_replying_buffer}')
break
# 处理数据流的主体
chunkjson = json.loads(chunk_decoded[6:])
status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
# 如果这里抛出异常一般是文本过长详情见get_full_error的输出
gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk_decoded[6:])['choices'][0]["delta"]["content"]
if has_content:
# 正常情况
gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
elif has_role:
# 一些第三方接口的出现这样的错误,兼容一下吧
continue
else:
# 一些垃圾第三方接口的出现这样的错误
gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
history[-1] = gpt_replying_buffer
chatbot[-1] = (history[-2], history[-1])
yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
@@ -280,9 +314,19 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
what_i_ask_now["role"] = "user"
what_i_ask_now["content"] = inputs
messages.append(what_i_ask_now)
model = llm_kwargs['llm_model'].strip('api2d-')
if model == "gpt-3.5-random": # 随机选择, 绕过openai访问频率限制
model = random.choice([
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-0301",
])
logging.info("Random select model:" + model)
payload = {
"model": llm_kwargs['llm_model'].strip('api2d-'),
"model": model,
"messages": messages,
"temperature": llm_kwargs['temperature'], # 1.0,
"top_p": llm_kwargs['top_p'], # 1.0,

View File

@@ -30,7 +30,7 @@ class GetONNXGLMHandle(LocalLLMHandle):
with open(os.path.expanduser('~/.cache/huggingface/token'), 'w') as f:
f.write(huggingface_token)
model_id = 'meta-llama/Llama-2-7b-chat-hf'
with ProxyNetworkActivate():
with ProxyNetworkActivate('Download_LLM'):
self._tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=huggingface_token)
# use fp16
model = AutoModelForCausalLM.from_pretrained(model_id, use_auth_token=huggingface_token).eval()

View File

@@ -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)

View File

@@ -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
@@ -109,6 +109,7 @@ class SparkRequestInstance():
code = data['header']['code']
if code != 0:
print(f'请求错误: {code}, {data}')
self.result_buf += str(data)
ws.close()
self.time_to_exit_event.set()
else:

View File

@@ -1,5 +1,4 @@
protobuf
transformers>=4.27.1
cpm_kernels
torch>=1.10
mdtex2html

View File

@@ -1,5 +1,4 @@
protobuf
transformers>=4.27.1
cpm_kernels
torch>=1.10
mdtex2html

View File

@@ -2,6 +2,5 @@ jittor >= 1.3.7.9
jtorch >= 0.1.3
torch
torchvision
transformers==4.26.1
pandas
jieba

View File

@@ -1,5 +1,4 @@
torch
transformers==4.25.1
sentencepiece
datasets
accelerate

View File

@@ -1,8 +1,8 @@
./docs/gradio-3.32.2-py3-none-any.whl
./docs/gradio-3.32.6-py3-none-any.whl
pydantic==1.10.11
tiktoken>=0.3.3
requests[socks]
transformers
transformers>=4.27.1
python-markdown-math
beautifulsoup4
prompt_toolkit
@@ -20,4 +20,4 @@ arxiv
rich
pypdf2==2.12.1
websocket-client
scipdf_parser==0.3
scipdf_parser>=0.3

View File

@@ -6,12 +6,18 @@
import os, sys
def validate_path(): dir_name = os.path.dirname(__file__); root_dir_assume = os.path.abspath(dir_name + '/..'); os.chdir(root_dir_assume); sys.path.append(root_dir_assume)
validate_path() # 返回项目根路径
from tests.test_utils import plugin_test
if __name__ == "__main__":
from tests.test_utils import plugin_test
# plugin_test(plugin='crazy_functions.函数动态生成->函数动态生成', main_input='交换图像的蓝色通道和红色通道', advanced_arg={"file_path_arg": "./build/ants.jpg"})
plugin_test(plugin='crazy_functions.Latex输出PDF结果->Latex翻译中文并重新编译PDF', main_input="2307.07522")
# plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep')
plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='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.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->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')

View File

@@ -74,7 +74,7 @@ def plugin_test(main_input, plugin, advanced_arg=None):
plugin_kwargs['plugin_kwargs'] = advanced_arg
my_working_plugin = silence_stdout(plugin)(**plugin_kwargs)
with Live(Markdown(""), auto_refresh=False) as live:
with Live(Markdown(""), auto_refresh=False, vertical_overflow="visible") as live:
for cookies, chat, hist, msg in my_working_plugin:
md_str = vt.chat_to_markdown_str(chat)
md = Markdown(md_str)

View File

@@ -9,6 +9,11 @@
box-shadow: none;
}
#input-plugin-group .secondary-wrap.svelte-aqlk7e.svelte-aqlk7e.svelte-aqlk7e {
border: none;
min-width: 0;
}
/* hide selector label */
#input-plugin-group .svelte-1gfkn6j {
visibility: hidden;
@@ -19,3 +24,91 @@
.wrap.svelte-xwlu1w {
min-height: var(--size-32);
}
/* status bar height */
.min.svelte-1yrv54 {
min-height: var(--size-12);
}
/* copy btn */
.message-btn-row {
width: 19px;
height: 19px;
position: absolute;
left: calc(100% + 3px);
top: 0;
display: flex;
justify-content: space-between;
}
/* .message-btn-row-leading, .message-btn-row-trailing {
display: inline-flex;
gap: 4px;
} */
.message-btn-row button {
font-size: 18px;
align-self: center;
align-items: center;
flex-wrap: nowrap;
white-space: nowrap;
display: inline-flex;
flex-direction: row;
gap: 4px;
padding-block: 2px !important;
}
/* Scrollbar Width */
::-webkit-scrollbar {
width: 12px;
}
/* Scrollbar Track */
::-webkit-scrollbar-track {
background: #f1f1f1;
border-radius: 12px;
}
/* Scrollbar Handle */
::-webkit-scrollbar-thumb {
background: #888;
border-radius: 12px;
}
/* Scrollbar Handle on hover */
::-webkit-scrollbar-thumb:hover {
background: #555;
}
/* input btns: clear, reset, stop */
#input-panel button {
min-width: min(80px, 100%);
}
/* input btns: clear, reset, stop */
#input-panel2 button {
min-width: min(80px, 100%);
}
#cbs {
background-color: var(--block-background-fill) !important;
}
#interact-panel .form {
border: hidden
}
.drag-area {
border: solid;
border-width: thin;
user-select: none;
padding-left: 2%;
}
.floating-component #input-panel2 {
border-top-left-radius: 0px;
border-top-right-radius: 0px;
border: solid;
border-width: thin;
border-top-width: 0;
}

View File

@@ -1,4 +1,105 @@
function ChatBotHeight() {
function gradioApp() {
// https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
const elems = document.getElementsByTagName('gradio-app');
const elem = elems.length == 0 ? document : elems[0];
if (elem !== document) {
elem.getElementById = function(id) {
return document.getElementById(id);
};
}
return elem.shadowRoot ? elem.shadowRoot : elem;
}
function setCookie(name, value, days) {
var expires = "";
if (days) {
var date = new Date();
date.setTime(date.getTime() + (days * 24 * 60 * 60 * 1000));
expires = "; expires=" + date.toUTCString();
}
document.cookie = name + "=" + value + expires + "; path=/";
}
function getCookie(name) {
var decodedCookie = decodeURIComponent(document.cookie);
var cookies = decodedCookie.split(';');
for (var i = 0; i < cookies.length; i++) {
var cookie = cookies[i].trim();
if (cookie.indexOf(name + "=") === 0) {
return cookie.substring(name.length + 1, cookie.length);
}
}
return null;
}
function addCopyButton(botElement) {
// https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
// Copy bot button
const copiedIcon = '<span><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" height=".8em" width=".8em" xmlns="http://www.w3.org/2000/svg"><polyline points="20 6 9 17 4 12"></polyline></svg></span>';
const copyIcon = '<span><svg stroke="currentColor" fill="none" stroke-width="2" viewBox="0 0 24 24" stroke-linecap="round" stroke-linejoin="round" height=".8em" width=".8em" xmlns="http://www.w3.org/2000/svg"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"></rect><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"></path></svg></span>';
const messageBtnColumnElement = botElement.querySelector('.message-btn-row');
if (messageBtnColumnElement) {
// Do something if .message-btn-column exists, for example, remove it
// messageBtnColumnElement.remove();
return;
}
var copyButton = document.createElement('button');
copyButton.classList.add('copy-bot-btn');
copyButton.setAttribute('aria-label', 'Copy');
copyButton.innerHTML = copyIcon;
copyButton.addEventListener('click', async () => {
const textToCopy = botElement.innerText;
try {
if ("clipboard" in navigator) {
await navigator.clipboard.writeText(textToCopy);
copyButton.innerHTML = copiedIcon;
setTimeout(() => {
copyButton.innerHTML = copyIcon;
}, 1500);
} else {
const textArea = document.createElement("textarea");
textArea.value = textToCopy;
document.body.appendChild(textArea);
textArea.select();
try {
document.execCommand('copy');
copyButton.innerHTML = copiedIcon;
setTimeout(() => {
copyButton.innerHTML = copyIcon;
}, 1500);
} catch (error) {
console.error("Copy failed: ", error);
}
document.body.removeChild(textArea);
}
} catch (error) {
console.error("Copy failed: ", error);
}
});
var messageBtnColumn = document.createElement('div');
messageBtnColumn.classList.add('message-btn-row');
messageBtnColumn.appendChild(copyButton);
botElement.appendChild(messageBtnColumn);
}
function chatbotContentChanged(attempt = 1, force = false) {
// https://github.com/GaiZhenbiao/ChuanhuChatGPT/tree/main/web_assets/javascript
for (var i = 0; i < attempt; i++) {
setTimeout(() => {
gradioApp().querySelectorAll('#gpt-chatbot .message-wrap .message.bot').forEach(addCopyButton);
}, i === 0 ? 0 : 200);
}
}
function chatbotAutoHeight(){
// 自动调整高度
function update_height(){
var { panel_height_target, chatbot_height, chatbot } = get_elements(true);
if (panel_height_target!=chatbot_height)
@@ -28,6 +129,15 @@ function ChatBotHeight() {
}, 50); // 每100毫秒执行一次
}
function GptAcademicJavaScriptInit(LAYOUT = "LEFT-RIGHT") {
chatbotIndicator = gradioApp().querySelector('#gpt-chatbot > div.wrap');
var chatbotObserver = new MutationObserver(() => {
chatbotContentChanged(1);
});
chatbotObserver.observe(chatbotIndicator, { attributes: true, childList: true, subtree: true });
if (LAYOUT === "LEFT-RIGHT") {chatbotAutoHeight();}
}
function get_elements(consider_state_panel=false) {
var chatbot = document.querySelector('#gpt-chatbot > div.wrap.svelte-18telvq');
if (!chatbot) {
@@ -36,14 +146,14 @@ function get_elements(consider_state_panel=false) {
const panel1 = document.querySelector('#input-panel').getBoundingClientRect();
const panel2 = document.querySelector('#basic-panel').getBoundingClientRect()
const panel3 = document.querySelector('#plugin-panel').getBoundingClientRect();
const panel4 = document.querySelector('#interact-panel').getBoundingClientRect();
// const panel4 = document.querySelector('#interact-panel').getBoundingClientRect();
const panel5 = document.querySelector('#input-panel2').getBoundingClientRect();
const panel_active = document.querySelector('#state-panel').getBoundingClientRect();
if (consider_state_panel || panel_active.height < 25){
document.state_panel_height = panel_active.height;
}
// 25 是chatbot的label高度, 16 是右侧的gap
var panel_height_target = panel1.height + panel2.height + panel3.height + panel4.height + panel5.height - 25 + 16*3;
var panel_height_target = panel1.height + panel2.height + panel3.height + 0 + 0 - 25 + 16*2;
// 禁止动态的state-panel高度影响
panel_height_target = panel_height_target + (document.state_panel_height-panel_active.height)
var panel_height_target = parseInt(panel_height_target);

View File

@@ -198,7 +198,7 @@
}
/* 小按钮 */
.sm.svelte-1ipelgc {
.sm {
font-family: "Microsoft YaHei UI", "Helvetica", "Microsoft YaHei", "ui-sans-serif", "sans-serif", "system-ui";
--button-small-text-weight: 600;
--button-small-text-size: 16px;
@@ -208,7 +208,7 @@
border-top-left-radius: 0px;
}
#plugin-panel .sm.svelte-1ipelgc {
#plugin-panel .sm {
font-family: "Microsoft YaHei UI", "Helvetica", "Microsoft YaHei", "ui-sans-serif", "sans-serif", "system-ui";
--button-small-text-weight: 400;
--button-small-text-size: 14px;

View File

@@ -57,11 +57,8 @@ def adjust_theme():
button_cancel_text_color_dark="white",
)
if LAYOUT=="TOP-DOWN":
js = ""
else:
with open('themes/common.js', 'r', encoding='utf8') as f:
js = f"<script>{f.read()}</script>"
with open('themes/common.js', 'r', encoding='utf8') as f:
js = f"<script>{f.read()}</script>"
# 添加一个萌萌的看板娘
if ADD_WAIFU:

View File

@@ -9,15 +9,15 @@
border-radius: 4px;
}
#plugin-panel .dropdown-arrow.svelte-p5edak {
width: 50px;
#plugin-panel .dropdown-arrow {
width: 25px;
}
#plugin-panel input.svelte-aqlk7e.svelte-aqlk7e.svelte-aqlk7e {
padding-left: 5px;
}
/* 小按钮 */
.sm.svelte-1ipelgc {
#basic-panel .sm {
font-family: "Microsoft YaHei UI", "Helvetica", "Microsoft YaHei", "ui-sans-serif", "sans-serif", "system-ui";
--button-small-text-weight: 600;
--button-small-text-size: 16px;
@@ -27,7 +27,7 @@
border-top-left-radius: 6px;
}
#plugin-panel .sm.svelte-1ipelgc {
#plugin-panel .sm {
font-family: "Microsoft YaHei UI", "Helvetica", "Microsoft YaHei", "ui-sans-serif", "sans-serif", "system-ui";
--button-small-text-weight: 400;
--button-small-text-size: 14px;

View File

@@ -57,11 +57,8 @@ def adjust_theme():
button_cancel_text_color_dark="white",
)
if LAYOUT=="TOP-DOWN":
js = ""
else:
with open('themes/common.js', 'r', encoding='utf8') as f:
js = f"<script>{f.read()}</script>"
with open('themes/common.js', 'r', encoding='utf8') as f:
js = f"<script>{f.read()}</script>"
# 添加一个萌萌的看板娘
if ADD_WAIFU:

52
themes/gradios.py Normal file
View File

@@ -0,0 +1,52 @@
import gradio as gr
import logging
from toolbox import get_conf, ProxyNetworkActivate
CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'LAYOUT')
def dynamic_set_theme(THEME):
set_theme = gr.themes.ThemeClass()
with ProxyNetworkActivate('Download_Gradio_Theme'):
logging.info('正在下载Gradio主题请稍等。')
if THEME.startswith('Huggingface-'): THEME = THEME.lstrip('Huggingface-')
if THEME.startswith('huggingface-'): THEME = THEME.lstrip('huggingface-')
set_theme = set_theme.from_hub(THEME.lower())
return set_theme
def adjust_theme():
try:
set_theme = gr.themes.ThemeClass()
with ProxyNetworkActivate('Download_Gradio_Theme'):
logging.info('正在下载Gradio主题请稍等。')
THEME, = get_conf('THEME')
if THEME.startswith('Huggingface-'): THEME = THEME.lstrip('Huggingface-')
if THEME.startswith('huggingface-'): THEME = THEME.lstrip('huggingface-')
set_theme = set_theme.from_hub(THEME.lower())
with open('themes/common.js', 'r', encoding='utf8') as f:
js = f"<script>{f.read()}</script>"
# 添加一个萌萌的看板娘
if ADD_WAIFU:
js += """
<script src="file=docs/waifu_plugin/jquery.min.js"></script>
<script src="file=docs/waifu_plugin/jquery-ui.min.js"></script>
<script src="file=docs/waifu_plugin/autoload.js"></script>
"""
gradio_original_template_fn = gr.routes.templates.TemplateResponse
def gradio_new_template_fn(*args, **kwargs):
res = gradio_original_template_fn(*args, **kwargs)
res.body = res.body.replace(b'</html>', f'{js}</html>'.encode("utf8"))
res.init_headers()
return res
gr.routes.templates.TemplateResponse = gradio_new_template_fn # override gradio template
except Exception as e:
set_theme = None
from toolbox import trimmed_format_exc
logging.error('gradio版本较旧, 不能自定义字体和颜色:', trimmed_format_exc())
return set_theme
# with open("themes/default.css", "r", encoding="utf-8") as f:
# advanced_css = f.read()
with open("themes/common.css", "r", encoding="utf-8") as f:
advanced_css = f.read()

View File

@@ -73,12 +73,8 @@ def adjust_theme():
chatbot_code_background_color_dark="*neutral_950",
)
js = ''
if LAYOUT=="TOP-DOWN":
js = ""
else:
with open('themes/common.js', 'r', encoding='utf8') as f:
js = f"<script>{f.read()}</script>"
with open('themes/common.js', 'r', encoding='utf8') as f:
js = f"<script>{f.read()}</script>"
# 添加一个萌萌的看板娘
if ADD_WAIFU:

View File

@@ -2,14 +2,22 @@ import gradio as gr
from toolbox import get_conf
THEME, = get_conf('THEME')
if THEME == 'Chuanhu-Small-and-Beautiful':
from .green import adjust_theme, advanced_css
theme_declaration = "<h2 align=\"center\" class=\"small\">[Chuanhu-Small-and-Beautiful主题]</h2>"
elif THEME == 'High-Contrast':
from .contrast import adjust_theme, advanced_css
theme_declaration = ""
else:
from .default import adjust_theme, advanced_css
theme_declaration = ""
def load_dynamic_theme(THEME):
adjust_dynamic_theme = None
if THEME == 'Chuanhu-Small-and-Beautiful':
from .green import adjust_theme, advanced_css
theme_declaration = "<h2 align=\"center\" class=\"small\">[Chuanhu-Small-and-Beautiful主题]</h2>"
elif THEME == 'High-Contrast':
from .contrast import adjust_theme, advanced_css
theme_declaration = ""
elif '/' in THEME:
from .gradios import adjust_theme, advanced_css
from .gradios import dynamic_set_theme
adjust_dynamic_theme = dynamic_set_theme(THEME)
theme_declaration = ""
else:
from .default import adjust_theme, advanced_css
theme_declaration = ""
return adjust_theme, advanced_css, theme_declaration, adjust_dynamic_theme
adjust_theme, advanced_css, theme_declaration, _ = load_dynamic_theme(THEME)

View File

@@ -5,6 +5,8 @@ import inspect
import re
import os
import gradio
import shutil
import glob
from latex2mathml.converter import convert as tex2mathml
from functools import wraps, lru_cache
pj = os.path.join
@@ -77,14 +79,24 @@ def ArgsGeneralWrapper(f):
}
chatbot_with_cookie = ChatBotWithCookies(cookies)
chatbot_with_cookie.write_list(chatbot)
if cookies.get('lock_plugin', None) is None:
# 正常状态
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
if len(args) == 0: # 插件通道
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, request)
else: # 对话通道,或者基础功能通道
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
else:
# 处理个别特殊插件的锁定状态
# 处理少数情况下的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, request)
# 判断一下用户是否错误地通过对话通道进入,如果是,则进行提醒
final_cookies = chatbot_with_cookie.get_cookies()
# len(args) != 0 代表“提交”键对话通道,或者基础功能通道
if len(args) != 0 and 'files_to_promote' in final_cookies and len(final_cookies['files_to_promote']) > 0:
chatbot_with_cookie.append(["检测到**滞留的缓存文档**,请及时处理。", "请及时点击“**保存当前对话**”获取所有滞留文档。"])
yield from update_ui(chatbot_with_cookie, final_cookies['history'], msg="检测到被滞留的缓存文档")
return decorated
@@ -94,7 +106,8 @@ def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
"""
assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时, 可用clear将其清空, 然后用for+append循环重新赋值。"
cookies = chatbot.get_cookies()
# 备份一份History作为记录
cookies.update({'history': history})
# 解决插件锁定时的界面显示问题
if cookies.get('lock_plugin', None):
label = cookies.get('llm_model', "") + " | " + "正在锁定插件" + cookies.get('lock_plugin', None)
@@ -171,7 +184,7 @@ def HotReload(f):
========================================================================
第二部分
其他小工具:
- write_results_to_file: 将结果写入markdown文件中
- write_history_to_file: 将结果写入markdown文件中
- regular_txt_to_markdown: 将普通文本转换为Markdown格式的文本。
- report_execption: 向chatbot中添加简单的意外错误信息
- text_divide_paragraph: 将文本按照段落分隔符分割开生成带有段落标签的HTML代码。
@@ -203,37 +216,7 @@ def get_reduce_token_percent(text):
return 0.5, '不详'
def write_results_to_file(history, file_name=None):
"""
将对话记录history以Markdown格式写入文件中。如果没有指定文件名则使用当前时间生成文件名。
"""
import os
import time
if file_name is None:
# file_name = time.strftime("chatGPT分析报告%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
file_name = 'GPT-Report-' + gen_time_str() + '.md'
os.makedirs('./gpt_log/', exist_ok=True)
with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
f.write('# GPT-Academic Report\n')
for i, content in enumerate(history):
try:
if type(content) != str: content = str(content)
except:
continue
if i % 2 == 0:
f.write('## ')
try:
f.write(content)
except:
# remove everything that cannot be handled by utf8
f.write(content.encode('utf-8', 'ignore').decode())
f.write('\n\n')
res = '以上材料已经被写入:\t' + os.path.abspath(f'./gpt_log/{file_name}')
print(res)
return res
def write_history_to_file(history, file_basename=None, file_fullname=None):
def write_history_to_file(history, file_basename=None, file_fullname=None, auto_caption=True):
"""
将对话记录history以Markdown格式写入文件中。如果没有指定文件名则使用当前时间生成文件名。
"""
@@ -241,9 +224,9 @@ def write_history_to_file(history, file_basename=None, file_fullname=None):
import time
if file_fullname is None:
if file_basename is not None:
file_fullname = os.path.join(get_log_folder(), file_basename)
file_fullname = pj(get_log_folder(), file_basename)
else:
file_fullname = os.path.join(get_log_folder(), f'GPT-Academic-{gen_time_str()}.md')
file_fullname = pj(get_log_folder(), f'GPT-Academic-{gen_time_str()}.md')
os.makedirs(os.path.dirname(file_fullname), exist_ok=True)
with open(file_fullname, 'w', encoding='utf8') as f:
f.write('# GPT-Academic Report\n')
@@ -252,7 +235,7 @@ def write_history_to_file(history, file_basename=None, file_fullname=None):
if type(content) != str: content = str(content)
except:
continue
if i % 2 == 0:
if i % 2 == 0 and auto_caption:
f.write('## ')
try:
f.write(content)
@@ -281,8 +264,7 @@ 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):
@@ -305,6 +287,7 @@ 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):
"""
@@ -359,19 +342,41 @@ 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
@@ -379,7 +384,7 @@ 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):
@@ -467,7 +472,7 @@ def extract_archive(file_path, dest_dir):
print("Successfully extracted rar archive to {}".format(dest_dir))
except:
print("Rar format requires additional dependencies to install")
return '\n\n解压失败! 需要安装pip install rarfile来解压rar文件'
return '\n\n解压失败! 需要安装pip install rarfile来解压rar文件。建议使用zip压缩格式。'
# 第三方库需要预先pip install py7zr
elif file_extension == '.7z':
@@ -497,7 +502,7 @@ def find_recent_files(directory):
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)
file_path = pj(directory, filename)
if file_path.endswith('.log'):
continue
created_time = os.path.getmtime(file_path)
@@ -512,59 +517,86 @@ def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
# 将文件复制一份到下载区
import shutil
if rename_file is None: rename_file = f'{gen_time_str()}-{os.path.basename(file)}'
new_path = os.path.join(get_log_folder(), rename_file)
new_path = pj(get_log_folder(), rename_file)
# 如果已经存在,先删除
if os.path.exists(new_path) and not os.path.samefile(new_path, file): os.remove(new_path)
# 把文件复制过去
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 chatbot is not None:
if 'files_to_promote' in chatbot._cookies: current = chatbot._cookies['files_to_promote']
else: current = []
chatbot._cookies.update({'files_to_promote': [new_path] + current})
return new_path
def disable_auto_promotion(chatbot):
chatbot._cookies.update({'files_to_promote': []})
return
def on_file_uploaded(files, chatbot, txt, txt2, checkboxes, cookies):
def is_the_upload_folder(string):
PATH_PRIVATE_UPLOAD, = get_conf('PATH_PRIVATE_UPLOAD')
pattern = r'^PATH_PRIVATE_UPLOAD/[A-Za-z0-9_-]+/\d{4}-\d{2}-\d{2}-\d{2}-\d{2}-\d{2}$'
pattern = pattern.replace('PATH_PRIVATE_UPLOAD', PATH_PRIVATE_UPLOAD)
if re.match(pattern, string): return True
else: return False
def del_outdated_uploads(outdate_time_seconds):
PATH_PRIVATE_UPLOAD, = get_conf('PATH_PRIVATE_UPLOAD')
current_time = time.time()
one_hour_ago = current_time - outdate_time_seconds
# Get a list of all subdirectories in the PATH_PRIVATE_UPLOAD folder
# Remove subdirectories that are older than one hour
for subdirectory in glob.glob(f'{PATH_PRIVATE_UPLOAD}/*/*'):
subdirectory_time = os.path.getmtime(subdirectory)
if subdirectory_time < one_hour_ago:
try: shutil.rmtree(subdirectory)
except: pass
return
def on_file_uploaded(request: gradio.Request, files, chatbot, txt, txt2, checkboxes, cookies):
"""
当文件被上传时的回调函数
"""
if len(files) == 0:
return chatbot, txt
import shutil
import os
import time
import glob
from toolbox import extract_archive
try:
shutil.rmtree('./private_upload/')
except:
pass
# 移除过时的旧文件从而节省空间&保护隐私
outdate_time_seconds = 60
del_outdated_uploads(outdate_time_seconds)
# 创建工作路径
user_name = "default" if not request.username else request.username
time_tag = gen_time_str()
os.makedirs(f'private_upload/{time_tag}', exist_ok=True)
err_msg = ''
PATH_PRIVATE_UPLOAD, = get_conf('PATH_PRIVATE_UPLOAD')
target_path_base = pj(PATH_PRIVATE_UPLOAD, user_name, time_tag)
os.makedirs(target_path_base, exist_ok=True)
# 逐个文件转移到目标路径
upload_msg = ''
for file in files:
file_origin_name = os.path.basename(file.orig_name)
shutil.copy(file.name, f'private_upload/{time_tag}/{file_origin_name}')
err_msg += extract_archive(f'private_upload/{time_tag}/{file_origin_name}',
dest_dir=f'private_upload/{time_tag}/{file_origin_name}.extract')
moved_files = [fp for fp in glob.glob('private_upload/**/*', recursive=True)]
if "底部输入区" in checkboxes:
txt = ""
txt2 = f'private_upload/{time_tag}'
this_file_path = pj(target_path_base, file_origin_name)
shutil.move(file.name, this_file_path)
upload_msg += extract_archive(file_path=this_file_path, dest_dir=this_file_path+'.extract')
# 整理文件集合
moved_files = [fp for fp in glob.glob(f'{target_path_base}/**/*', recursive=True)]
if "浮动输入区" in checkboxes:
txt, txt2 = "", target_path_base
else:
txt = f'private_upload/{time_tag}'
txt2 = ""
txt, txt2 = target_path_base, ""
# 输出消息
moved_files_str = '\t\n\n'.join(moved_files)
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])
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'+upload_msg])
# 记录近期文件
cookies.update({
'most_recent_uploaded': {
'path': f'private_upload/{time_tag}',
'path': target_path_base,
'time': time.time(),
'time_str': time_tag
}})
@@ -573,11 +605,12 @@ def on_file_uploaded(files, chatbot, txt, txt2, checkboxes, cookies):
def on_report_generated(cookies, files, chatbot):
from toolbox import find_recent_files
PATH_LOGGING, = get_conf('PATH_LOGGING')
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')
report_files = find_recent_files(PATH_LOGGING)
if len(report_files) == 0:
return cookies, None, chatbot
# files.extend(report_files)
@@ -588,10 +621,20 @@ def on_report_generated(cookies, files, chatbot):
def load_chat_cookies():
API_KEY, LLM_MODEL, AZURE_API_KEY = get_conf('API_KEY', 'LLM_MODEL', 'AZURE_API_KEY')
DARK_MODE, NUM_CUSTOM_BASIC_BTN = get_conf('DARK_MODE', 'NUM_CUSTOM_BASIC_BTN')
if is_any_api_key(AZURE_API_KEY):
if is_any_api_key(API_KEY): API_KEY = API_KEY + ',' + AZURE_API_KEY
else: API_KEY = AZURE_API_KEY
return {'api_key': API_KEY, 'llm_model': LLM_MODEL}
customize_fn_overwrite_ = {}
for k in range(NUM_CUSTOM_BASIC_BTN):
customize_fn_overwrite_.update({
"自定义按钮" + str(k+1):{
"Title": r"",
"Prefix": r"请在自定义菜单中定义提示词前缀.",
"Suffix": r"请在自定义菜单中定义提示词后缀",
}
})
return {'api_key': API_KEY, 'llm_model': LLM_MODEL, 'customize_fn_overwrite': customize_fn_overwrite_}
def is_openai_api_key(key):
CUSTOM_API_KEY_PATTERN, = get_conf('CUSTOM_API_KEY_PATTERN')
@@ -887,34 +930,35 @@ def zip_folder(source_folder, dest_folder, zip_name):
return
# Create the name for the zip file
zip_file = os.path.join(dest_folder, zip_name)
zip_file = pj(dest_folder, zip_name)
# Create a ZipFile object
with zipfile.ZipFile(zip_file, 'w', zipfile.ZIP_DEFLATED) as zipf:
# Walk through the source folder and add files to the zip file
for foldername, subfolders, filenames in os.walk(source_folder):
for filename in filenames:
filepath = os.path.join(foldername, filename)
filepath = pj(foldername, filename)
zipf.write(filepath, arcname=os.path.relpath(filepath, source_folder))
# Move the zip file to the destination folder (if it wasn't already there)
if os.path.dirname(zip_file) != dest_folder:
os.rename(zip_file, os.path.join(dest_folder, os.path.basename(zip_file)))
zip_file = os.path.join(dest_folder, os.path.basename(zip_file))
os.rename(zip_file, pj(dest_folder, os.path.basename(zip_file)))
zip_file = pj(dest_folder, os.path.basename(zip_file))
print(f"Zip file created at {zip_file}")
def zip_result(folder):
t = gen_time_str()
zip_folder(folder, './gpt_log/', f'{t}-result.zip')
return pj('./gpt_log/', f'{t}-result.zip')
zip_folder(folder, get_log_folder(), f'{t}-result.zip')
return pj(get_log_folder(), f'{t}-result.zip')
def gen_time_str():
import time
return time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime())
def get_log_folder(user='default', plugin_name='shared'):
_dir = os.path.join(os.path.dirname(__file__), 'gpt_log', user, plugin_name)
PATH_LOGGING, = get_conf('PATH_LOGGING')
_dir = pj(PATH_LOGGING, user, plugin_name)
if not os.path.exists(_dir): os.makedirs(_dir)
return _dir
@@ -922,7 +966,19 @@ class ProxyNetworkActivate():
"""
这段代码定义了一个名为TempProxy的空上下文管理器, 用于给一小段代码上代理
"""
def __init__(self, task=None) -> None:
self.task = task
if not task:
# 不给定task, 那么我们默认代理生效
self.valid = True
else:
# 给定了task, 我们检查一下
from toolbox import get_conf
WHEN_TO_USE_PROXY, = get_conf('WHEN_TO_USE_PROXY')
self.valid = (task in WHEN_TO_USE_PROXY)
def __enter__(self):
if not self.valid: return self
from toolbox import get_conf
proxies, = get_conf('proxies')
if 'no_proxy' in os.environ: os.environ.pop('no_proxy')

View File

@@ -1,5 +1,5 @@
{
"version": 3.50,
"version": 3.55,
"show_feature": true,
"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"
"new_feature": "重新编译Gradio优化使用体验 <-> 新增动态代码解释器CodeInterpreter <-> 增加文本回答复制按钮 <-> 细分代理场合 <-> 支持动态选择不同界面主题 <-> 提高稳定性&解决多用户冲突问题 <-> 支持插件分类和更多UI皮肤外观 <-> 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"
}