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version3.5
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@@ -17,7 +17,7 @@ WORKDIR /gpt
|
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# 安装大部分依赖,利用Docker缓存加速以后的构建
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COPY requirements.txt ./
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COPY ./docs/gradio-3.32.2-py3-none-any.whl ./docs/gradio-3.32.2-py3-none-any.whl
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COPY ./docs/gradio-3.32.6-py3-none-any.whl ./docs/gradio-3.32.6-py3-none-any.whl
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RUN pip3 install -r requirements.txt
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@@ -1,6 +1,6 @@
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> **Note**
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>
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> 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**
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> 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**
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>
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> `pip install -r requirements.txt`
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@@ -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
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### II:版本:
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- version 3.60(todo): 优化虚空终端,引入code interpreter和更多插件
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- version 3.55: 重构前端界面,引入悬浮窗口与菜单栏
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- version 3.54: 新增动态代码解释器(Code Interpreter)(待完善)
|
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- 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
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- 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
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- version 3.49: 支持百度千帆平台和文心一言
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@@ -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
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- version 2.0: 引入模块化函数插件
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- version 1.0: 基础功能
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gpt_academic开发者QQ群-2:610599535
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GPT Academic开发者QQ群:`610599535`
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- 已知问题
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- 某些浏览器翻译插件干扰此软件前端的运行
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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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36
config.py
36
config.py
@@ -46,6 +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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@@ -58,7 +59,10 @@ CODE_HIGHLIGHT = True
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# 窗口布局
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LAYOUT = "LEFT-RIGHT" # "LEFT-RIGHT"(左右布局) # "TOP-DOWN"(上下布局)
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DARK_MODE = True # 暗色模式 / 亮色模式
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|
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|
||||
# 暗色模式 / 亮色模式
|
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DARK_MODE = True
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|
||||
|
||||
# 发送请求到OpenAI后,等待多久判定为超时
|
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@@ -74,14 +78,14 @@ 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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|
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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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# 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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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", "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", "gpt-3.5-random"
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# "spark", "sparkv2", "chatglm_onnx", "claude-1-100k", "claude-2", "internlm", "jittorllms_pangualpha", "jittorllms_llama"]
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|
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|
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@@ -121,6 +125,11 @@ AUTHENTICATION = []
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CUSTOM_PATH = "/"
|
||||
|
||||
|
||||
# HTTPS 秘钥和证书(不需要修改)
|
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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
|
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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
|
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AZURE_ENGINE = "填入你亲手写的部署名" # 读 docs\use_azure.md
|
||||
|
||||
|
||||
# 使用Newbing
|
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# 使用Newbing (不推荐使用,未来将删除)
|
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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
|
||||
│
|
||||
|
||||
@@ -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
|
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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. " +
|
||||
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
|
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"Suffix": r"",
|
||||
# 按钮颜色 (默认 secondary)
|
||||
@@ -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? " +
|
||||
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"
|
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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. "
|
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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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@@ -89,8 +91,15 @@ def handle_core_functionality(additional_fn, inputs, history, chatbot):
|
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import core_functional
|
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importlib.reload(core_functional) # 热更新prompt
|
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core_functional = core_functional.get_core_functions()
|
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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)
|
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inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
|
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if core_functional[additional_fn].get("AutoClearHistory", False):
|
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history = []
|
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return inputs, history
|
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addition = chatbot._cookies['customize_fn_overwrite']
|
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if additional_fn in addition:
|
||||
# 自定义功能
|
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inputs = addition[additional_fn]["Prefix"] + inputs + addition[additional_fn]["Suffix"]
|
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return inputs, history
|
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else:
|
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# 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)
|
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inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]
|
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if core_functional[additional_fn].get("AutoClearHistory", False):
|
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history = []
|
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return inputs, history
|
||||
|
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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
|
||||
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": "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)
|
||||
},
|
||||
|
||||
# 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
|
||||
|
||||
@@ -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()
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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)
|
||||
|
||||
70
crazy_functions/gen_fns/gen_fns_shared.py
Normal file
70
crazy_functions/gen_fns/gen_fns_shared.py
Normal 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()
|
||||
@@ -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
|
||||
|
||||
@@ -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)
|
||||
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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
Normal file
252
crazy_functions/函数动态生成.py
Normal 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"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):
|
||||
|
||||
@@ -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
|
||||
|
||||
|
||||
@@ -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)
|
||||
|
||||
@@ -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"
|
||||
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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 . .
|
||||
|
||||
Binary file not shown.
@@ -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"
|
||||
}
|
||||
@@ -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",
|
||||
|
||||
@@ -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"
|
||||
}
|
||||
@@ -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",
|
||||
|
||||
@@ -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
257
main.py
@@ -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, 但推荐上传压缩文件(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,
|
||||
|
||||
@@ -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,
|
||||
|
||||
@@ -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:
|
||||
|
||||
@@ -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,
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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')
|
||||
|
||||
|
||||
@@ -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)
|
||||
|
||||
@@ -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;
|
||||
}
|
||||
116
themes/common.js
116
themes/common.js
@@ -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);
|
||||
|
||||
@@ -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;
|
||||
|
||||
@@ -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 += """
|
||||
|
||||
@@ -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;
|
||||
|
||||
@@ -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:
|
||||
|
||||
@@ -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 += """
|
||||
|
||||
@@ -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:
|
||||
|
||||
@@ -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)
|
||||
31
toolbox.py
31
toolbox.py
@@ -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')
|
||||
|
||||
4
version
4
version
@@ -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"
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user