镜像自地址
https://github.com/binary-husky/gpt_academic.git
已同步 2025-12-06 06:26:47 +00:00
比较提交
30 次代码提交
version3.5
...
version3.5
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@@ -155,11 +155,13 @@ def auto_update(raise_error=False):
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def warm_up_modules():
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print('正在执行一些模块的预热...')
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from toolbox import ProxyNetworkActivate
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from request_llm.bridge_all import model_info
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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enc.encode("模块预热", disallowed_special=())
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enc = model_info["gpt-4"]['tokenizer']
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enc.encode("模块预热", disallowed_special=())
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with ProxyNetworkActivate("Warmup_Modules"):
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enc = model_info["gpt-3.5-turbo"]['tokenizer']
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enc.encode("模块预热", disallowed_special=())
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enc = model_info["gpt-4"]['tokenizer']
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enc.encode("模块预热", disallowed_special=())
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if __name__ == '__main__':
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import os
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@@ -46,7 +46,7 @@ DEFAULT_WORKER_NUM = 3
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# 色彩主题, 可选 ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast"]
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# 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", ...]
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THEME = "Default"
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AVAIL_THEMES = ["Default", "Chuanhu-Small-and-Beautiful", "High-Contrast", "Gstaff/Xkcd", "NoCrypt/Miku"]
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# 对话窗的高度 (仅在LAYOUT="TOP-DOWN"时生效)
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CHATBOT_HEIGHT = 1115
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@@ -74,13 +74,13 @@ MAX_RETRY = 2
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# 插件分类默认选项
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DEFAULT_FN_GROUPS = ['对话', '编程', '学术']
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DEFAULT_FN_GROUPS = ['对话', '编程', '学术', '智能体']
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# 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 )
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LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
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AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo",
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"gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
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"gpt-4", "gpt-4-32k", "azure-gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
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# 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",
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# "spark", "sparkv2", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
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@@ -183,6 +183,9 @@ ALLOW_RESET_CONFIG = False
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PATH_PRIVATE_UPLOAD = "private_upload"
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# 日志文件夹的位置,请勿修改
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PATH_LOGGING = "gpt_log"
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# 除了连接OpenAI之外,还有哪些场合允许使用代理,请勿修改
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WHEN_TO_USE_PROXY = ["Download_LLM", "Download_Gradio_Theme", "Connect_Grobid", "Warmup_Modules"]
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"""
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在线大模型配置关联关系示意图
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@@ -11,7 +11,8 @@ def get_core_functions():
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# 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
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"Prefix": r"Below is a paragraph from an academic paper. Polish the writing to meet the academic style, " +
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r"improve the spelling, grammar, clarity, concision and overall readability. When necessary, rewrite the whole sentence. " +
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r"Furthermore, list all modification and explain the reasons to do so in markdown table." + "\n\n",
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r"Firstly, you should provide the polished paragraph. "
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r"Secondly, you should list all your modification and explain the reasons to do so in markdown table." + "\n\n",
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# 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
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"Suffix": r"",
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# 按钮颜色 (默认 secondary)
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@@ -27,17 +28,18 @@ def get_core_functions():
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"Suffix": r"",
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},
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"查找语法错误": {
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"Prefix": r"Can you help me ensure that the grammar and the spelling is correct? " +
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r"Do not try to polish the text, if no mistake is found, tell me that this paragraph is good." +
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r"If you find grammar or spelling mistakes, please list mistakes you find in a two-column markdown table, " +
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r"put the original text the first column, " +
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r"put the corrected text in the second column and highlight the key words you fixed.""\n"
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"Prefix": r"Help me ensure that the grammar and the spelling is correct. "
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r"Do not try to polish the text, if no mistake is found, tell me that this paragraph is good. "
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r"If you find grammar or spelling mistakes, please list mistakes you find in a two-column markdown table, "
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r"put the original text the first column, "
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r"put the corrected text in the second column and highlight the key words you fixed. "
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r"Finally, please provide the proofreaded text.""\n\n"
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r"Example:""\n"
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r"Paragraph: How is you? Do you knows what is it?""\n"
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r"| Original sentence | Corrected sentence |""\n"
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r"| :--- | :--- |""\n"
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r"| How **is** you? | How **are** you? |""\n"
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r"| Do you **knows** what **is** **it**? | Do you **know** what **it** **is** ? |""\n"
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r"| Do you **knows** what **is** **it**? | Do you **know** what **it** **is** ? |""\n\n"
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r"Below is a paragraph from an academic paper. "
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r"You need to report all grammar and spelling mistakes as the example before."
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+ "\n\n",
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@@ -6,6 +6,7 @@ def get_crazy_functions():
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from crazy_functions.生成函数注释 import 批量生成函数注释
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from crazy_functions.解析项目源代码 import 解析项目本身
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from crazy_functions.解析项目源代码 import 解析一个Python项目
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from crazy_functions.解析项目源代码 import 解析一个Matlab项目
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from crazy_functions.解析项目源代码 import 解析一个C项目的头文件
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from crazy_functions.解析项目源代码 import 解析一个C项目
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from crazy_functions.解析项目源代码 import 解析一个Golang项目
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@@ -38,7 +39,7 @@ def get_crazy_functions():
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function_plugins = {
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"虚空终端": {
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"Group": "对话|编程|学术",
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"Group": "对话|编程|学术|智能体",
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"Color": "stop",
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"AsButton": True,
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"Function": HotReload(虚空终端)
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@@ -77,6 +78,13 @@ def get_crazy_functions():
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"Info": "批量总结word文档 | 输入参数为路径",
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"Function": HotReload(总结word文档)
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},
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"解析整个Matlab项目": {
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"Group": "编程",
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"Color": "stop",
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"AsButton": False,
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"Info": "解析一个Matlab项目的所有源文件(.m) | 输入参数为路径",
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"Function": HotReload(解析一个Matlab项目)
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},
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"解析整个C++项目头文件": {
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"Group": "编程",
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"Color": "stop",
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@@ -243,20 +251,23 @@ def get_crazy_functions():
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"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",
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"Function": HotReload(Latex中文润色)
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},
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"Latex项目全文中译英(输入路径或上传压缩包)": {
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"Group": "学术",
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"Color": "stop",
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"AsButton": False, # 加入下拉菜单中
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"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",
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"Function": HotReload(Latex中译英)
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},
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"Latex项目全文英译中(输入路径或上传压缩包)": {
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"Group": "学术",
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"Color": "stop",
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"AsButton": False, # 加入下拉菜单中
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"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",
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"Function": HotReload(Latex英译中)
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},
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# 被新插件取代
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# "Latex项目全文中译英(输入路径或上传压缩包)": {
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# "Group": "学术",
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# "Color": "stop",
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# "AsButton": False, # 加入下拉菜单中
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# "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",
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# "Function": HotReload(Latex中译英)
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# },
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# "Latex项目全文英译中(输入路径或上传压缩包)": {
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# "Group": "学术",
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# "Color": "stop",
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||||
# "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",
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# "Function": HotReload(Latex英译中)
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# },
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"批量Markdown中译英(输入路径或上传压缩包)": {
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"Group": "编程",
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"Color": "stop",
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@@ -513,6 +524,18 @@ def get_crazy_functions():
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except:
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print('Load function plugin failed')
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try:
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from crazy_functions.函数动态生成 import 函数动态生成
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function_plugins.update({
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"动态代码解释器(CodeInterpreter)": {
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"Group": "智能体",
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"Color": "stop",
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"AsButton": False,
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"Function": HotReload(函数动态生成)
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}
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})
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except:
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print('Load function plugin failed')
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# try:
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# from crazy_functions.CodeInterpreter import 虚空终端CodeInterpreter
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@@ -53,14 +53,14 @@ def 知识库问答(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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print('Checking Text2vec ...')
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from langchain.embeddings.huggingface import HuggingFaceEmbeddings
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with ProxyNetworkActivate(): # 临时地激活代理网络
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with ProxyNetworkActivate('Download_LLM'): # 临时地激活代理网络
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HuggingFaceEmbeddings(model_name="GanymedeNil/text2vec-large-chinese")
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# < -------------------构建知识库--------------- >
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chatbot.append(['<br/>'.join(file_manifest), "正在构建知识库..."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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print('Establishing knowledge archive ...')
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with ProxyNetworkActivate(): # 临时地激活代理网络
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with ProxyNetworkActivate('Download_LLM'): # 临时地激活代理网络
|
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kai = knowledge_archive_interface()
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kai.feed_archive(file_manifest=file_manifest, id=kai_id)
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kai_files = kai.get_loaded_file()
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|
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@@ -79,7 +79,7 @@ def move_project(project_folder, arxiv_id=None):
|
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shutil.copytree(src=project_folder, dst=new_workfolder)
|
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return new_workfolder
|
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|
||||
def arxiv_download(chatbot, history, txt):
|
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def arxiv_download(chatbot, history, txt, allow_cache=True):
|
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def check_cached_translation_pdf(arxiv_id):
|
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translation_dir = pj(ARXIV_CACHE_DIR, arxiv_id, 'translation')
|
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if not os.path.exists(translation_dir):
|
||||
@@ -116,7 +116,7 @@ def arxiv_download(chatbot, history, txt):
|
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arxiv_id = url_.split('/abs/')[-1]
|
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if 'v' in arxiv_id: arxiv_id = arxiv_id[:10]
|
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cached_translation_pdf = check_cached_translation_pdf(arxiv_id)
|
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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
|
||||
|
||||
@@ -651,7 +651,7 @@ 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 +807,10 @@ 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)
|
||||
|
||||
@@ -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()
|
||||
@@ -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:
|
||||
|
||||
252
crazy_functions/函数动态生成.py
普通文件
252
crazy_functions/函数动态生成.py
普通文件
@@ -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"第 {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
|
||||
|
||||
@@ -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)
|
||||
|
||||
@@ -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):
|
||||
|
||||
@@ -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
|
||||
# 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
|
||||
|
||||
@@ -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 ↓↓↓
|
||||
```
|
||||
|
||||
|
||||
|
||||
40
main.py
40
main.py
@@ -8,12 +8,13 @@ def main():
|
||||
# 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')
|
||||
|
||||
# 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),"
|
||||
@@ -59,6 +60,7 @@ def main():
|
||||
cancel_handles = []
|
||||
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, secret_font = gr.Textbox(visible=False), gr.Textbox(visible=False)
|
||||
cookies = gr.State(load_chat_cookies())
|
||||
with gr_L1():
|
||||
with gr_L2(scale=2, elem_id="gpt-chat"):
|
||||
@@ -123,7 +125,8 @@ def main():
|
||||
max_length_sl = gr.Slider(minimum=256, maximum=8192, value=4096, step=1, interactive=True, label="Local LLM MaxLength",)
|
||||
checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区", "底部输入区", "输入清除键", "插件参数区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
|
||||
md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False)
|
||||
dark_mode_btn = gr.Button("Toggle Dark Mode ☀", variant="secondary").style(size="sm")
|
||||
theme_dropdown = gr.Dropdown(AVAIL_THEMES, value=THEME, label="更换UI主题").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'));
|
||||
@@ -197,9 +200,37 @@ def main():
|
||||
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
|
||||
@@ -235,7 +266,7 @@ 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();}')
|
||||
demo.load(lambda: 0, inputs=None, outputs=None, _js='()=>{GptAcademicJavaScriptInit();}')
|
||||
|
||||
# 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():
|
||||
@@ -254,6 +285,7 @@ def main():
|
||||
|
||||
auto_opentab_delay()
|
||||
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
|
||||
quiet=True,
|
||||
server_name="0.0.0.0",
|
||||
server_port=PORT,
|
||||
favicon_path="docs/logo.png",
|
||||
|
||||
@@ -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 +126,15 @@ 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,
|
||||
},
|
||||
|
||||
# azure openai
|
||||
"azure-gpt-3.5":{
|
||||
"fn_with_ui": chatgpt_ui,
|
||||
@@ -135,6 +145,15 @@ 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,
|
||||
|
||||
@@ -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:
|
||||
|
||||
@@ -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()
|
||||
|
||||
@@ -1,5 +1,4 @@
|
||||
protobuf
|
||||
transformers>=4.27.1
|
||||
cpm_kernels
|
||||
torch>=1.10
|
||||
mdtex2html
|
||||
|
||||
@@ -1,5 +1,4 @@
|
||||
protobuf
|
||||
transformers>=4.27.1
|
||||
cpm_kernels
|
||||
torch>=1.10
|
||||
mdtex2html
|
||||
|
||||
@@ -2,6 +2,5 @@ jittor >= 1.3.7.9
|
||||
jtorch >= 0.1.3
|
||||
torch
|
||||
torchvision
|
||||
transformers==4.26.1
|
||||
pandas
|
||||
jieba
|
||||
@@ -1,5 +1,4 @@
|
||||
torch
|
||||
transformers==4.25.1
|
||||
sentencepiece
|
||||
datasets
|
||||
accelerate
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
pydantic==1.10.11
|
||||
tiktoken>=0.3.3
|
||||
requests[socks]
|
||||
transformers
|
||||
transformers>=4.27.1
|
||||
python-markdown-math
|
||||
beautifulsoup4
|
||||
prompt_toolkit
|
||||
|
||||
@@ -6,11 +6,14 @@
|
||||
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.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')
|
||||
|
||||
|
||||
@@ -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)
|
||||
|
||||
@@ -23,4 +23,63 @@
|
||||
/* 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%);
|
||||
}
|
||||
@@ -1,4 +1,86 @@
|
||||
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 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 GptAcademicJavaScriptInit() {
|
||||
chatbotIndicator = gradioApp().querySelector('#gpt-chatbot > div.wrap');
|
||||
var chatbotObserver = new MutationObserver(() => {
|
||||
chatbotContentChanged(1);
|
||||
});
|
||||
chatbotObserver.observe(chatbotIndicator, { attributes: true, childList: true, subtree: true });
|
||||
|
||||
function update_height(){
|
||||
var { panel_height_target, chatbot_height, chatbot } = get_elements(true);
|
||||
if (panel_height_target!=chatbot_height)
|
||||
|
||||
@@ -3,11 +3,20 @@ 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-')
|
||||
|
||||
@@ -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)
|
||||
13
toolbox.py
13
toolbox.py
@@ -527,6 +527,7 @@ def promote_file_to_downloadzone(file, rename_file=None, chatbot=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': []})
|
||||
@@ -955,7 +956,19 @@ 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')
|
||||
|
||||
4
version
4
version
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"version": 3.53,
|
||||
"version": 3.54,
|
||||
"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": "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"
|
||||
}
|
||||
|
||||
在新工单中引用
屏蔽一个用户