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62 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
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
51 changed files with 1443 additions and 225 deletions

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`
@@ -310,6 +310,8 @@ Tip不指定文件直接点击 `载入对话历史存档` 可以查看历史h
### II版本:
- version 3.60todo: 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
@@ -331,7 +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

@@ -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

@@ -46,6 +46,7 @@ DEFAULT_WORKER_NUM = 3
# 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)
@@ -58,7 +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
@@ -74,14 +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",
AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo",
"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"]
@@ -121,6 +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 = ""
@@ -136,7 +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
@@ -173,17 +182,30 @@ 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",
]
# 是否允许通过自然语言描述修改本页的配置,该功能具有一定的危险性,默认关闭
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
@@ -38,7 +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)
@@ -77,6 +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",
@@ -182,10 +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": {
@@ -243,20 +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",
@@ -384,7 +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,
@@ -429,7 +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,
@@ -489,11 +502,11 @@ 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)
}
})
@@ -513,19 +526,19 @@ def get_crazy_functions():
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.CodeInterpreter import 虚空终端CodeInterpreter
# function_plugins.update({
# "CodeInterpreter开发中仅供测试": {
# "Group": "编程|对话",
# "Color": "stop",
# "AsButton": False,
# "Function": HotReload(虚空终端CodeInterpreter)
# }
# })
# except:
# print('Load function plugin failed')
# try:
# from crazy_functions.chatglm微调工具 import 微调数据集生成

View File

@@ -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()

View File

@@ -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):
@@ -116,7 +116,7 @@ def arxiv_download(chatbot, history, txt):
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

View File

@@ -69,12 +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
@@ -193,6 +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 = ""
@@ -201,7 +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
@@ -275,7 +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
@@ -301,7 +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
@@ -651,7 +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
@@ -807,3 +813,10 @@ class construct_html():
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

@@ -342,10 +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

View File

@@ -1,4 +1,106 @@
import time, logging, 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():
@@ -66,12 +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)
@@ -79,12 +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

@@ -2,6 +2,8 @@ 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
@@ -12,13 +14,13 @@ 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:
@@ -29,7 +31,8 @@ def parse_pdf(pdf_path, grobid_url):
import scipdf # pip install scipdf_parser
if grobid_url.endswith('/'): grobid_url = grobid_url.rstrip('/')
try:
article_dict = scipdf.parse_pdf_to_dict(pdf_path, grobid_url=grobid_url)
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:

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

@@ -102,7 +102,7 @@ def 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwa
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)

View File

@@ -136,6 +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 = []
@@ -81,8 +94,9 @@ class InterviewAssistant(AliyunASR):
self.capture_interval = 0.5 # second
self.stop = False
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.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()
@@ -157,14 +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:
@@ -183,7 +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

@@ -26,7 +26,13 @@ def get_meta_information(url, chatbot, history):
'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'
}
session.proxies.update(proxies)
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)

View File

@@ -1,4 +1,28 @@
#【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.
## ===================================================
## ===================================================
## 【方案零】 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
@@ -8,10 +32,10 @@ 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
# 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", } '
# 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 '
@@ -27,7 +51,7 @@ services:
THEME: ' Chuanhu-Small-and-Beautiful '
ALIYUN_ACCESSKEY: ' LTAI5t6BrFUzxRXVGUWnekh1 '
ALIYUN_SECRET: ' eHmI20SVWIwQZxCiTD2bGQVspP9i68 '
# LOCAL_MODEL_DEVICE: ' cuda '
# LOCAL_MODEL_DEVICE: ' cuda '
# 加载英伟达显卡运行时
# runtime: nvidia
@@ -39,10 +63,14 @@ services:
# count: 1
# capabilities: [gpu]
# 与宿主的网络融合
# 【WEB_PORT暴露方法1: 适用于Linux】与宿主的网络融合
network_mode: "host"
# 不使用代理网络拉取最新代码
# 【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"

View File

@@ -13,21 +13,20 @@ 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 nougat-ocr
RUN python3 -m pip install rarfile py7zr
RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
RUN python3 -m pip install 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 https://github.com/OpenLMLab/MOSS.git request_llm/moss
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

View File

@@ -5,15 +5,16 @@
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 moviepy pdfminer
RUN pip3 install zh_langchain==0.2.1
RUN pip3 install python-docx pdfminer
RUN pip3 install nougat-ocr
RUN pip3 install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
# 装载项目文件
COPY . .

View File

@@ -322,7 +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",
@@ -2513,5 +2513,141 @@
"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"
"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

@@ -1007,7 +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",

View File

@@ -90,5 +90,7 @@
"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PDF_基于NOUGAT": "ParsePDF_NOUGAT",
"解析一个Matlab项目": "AnalyzeAMatlabProject",
"函数动态生成": "DynamicFunctionGeneration"
}

View File

@@ -346,7 +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",

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 ↓↓↓
```

257
main.py
View File

@@ -1,23 +1,37 @@
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, PATH_LOGGING = get_conf('ENABLE_AUDIO', 'AUTO_CLEAR_TXT', 'PATH_LOGGING')
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
@@ -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 = []
@@ -115,15 +139,29 @@ 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)
dark_mode_btn = gr.Button("Toggle Dark Mode ☀", variant="secondary").style(size="sm")
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'));
@@ -132,30 +170,113 @@ def main():
}
}""",
)
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]
@@ -179,8 +300,12 @@ 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
@@ -190,16 +315,45 @@ def main():
# 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
@@ -235,26 +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

@@ -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

@@ -18,6 +18,7 @@ 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
@@ -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):
"""
@@ -191,7 +207,9 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
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
@@ -199,15 +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 + chunkjson['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
@@ -288,9 +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

@@ -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

View File

@@ -6,11 +6,16 @@
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.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.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')

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;
@@ -23,4 +28,87 @@
/* 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

@@ -57,12 +57,9 @@ 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:
js += """

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:

View File

@@ -3,23 +3,29 @@ 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():
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())
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:
js += """

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

@@ -2,17 +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 = ""
elif '/' in THEME:
from .gradios 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

@@ -472,7 +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':
@@ -523,10 +523,11 @@ def promote_file_to_downloadzone(file, rename_file=None, chatbot=None):
# 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': []})
@@ -580,7 +581,7 @@ def on_file_uploaded(request: gradio.Request, files, chatbot, txt, txt2, checkbo
# 整理文件集合
moved_files = [fp for fp in glob.glob(f'{target_path_base}/**/*', recursive=True)]
if "底部输入区" in checkboxes:
if "浮动输入区" in checkboxes:
txt, txt2 = "", target_path_base
else:
txt, txt2 = target_path_base, ""
@@ -620,10 +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')
@@ -955,7 +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": 3.53,
"version": 3.55,
"show_feature": true,
"new_feature": "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"
"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"
}