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@@ -2,9 +2,9 @@
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# ChatGPT 学术优化
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**如果喜欢这个项目,请给它一个Star;如果你发明了更好用的学术快捷键,欢迎发issue或者pull requests(dev分支)**
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**如果喜欢这个项目,请给它一个Star;如果你发明了更好用的快捷键或函数插件,欢迎发issue或者pull requests(dev分支)**
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If you like this project, please give it a Star. If you've come up with more useful academic shortcuts, feel free to open an issue or pull request (to `dev` branch).
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If you like this project, please give it a Star. If you've come up with more useful academic shortcuts or functional plugins, feel free to open an issue or pull request (to `dev` branch).
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```
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代码中参考了很多其他优秀项目中的设计,主要包括:
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@@ -20,11 +20,11 @@ https://github.com/polarwinkel/mdtex2html
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> **Note**
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>
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> 1.请注意只有“红颜色”标识的函数插件(按钮)才支持读取文件。目前暂不能完善地支持pdf/word格式文献的翻译解读,相关函数函件正在测试中。
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> 1.请注意只有“红颜色”标识的函数插件(按钮)才支持读取文件。目前对pdf/word格式文件的支持插件正在逐步完善中,需要更多developer的帮助。
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>
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> 2.本项目中每个文件的功能都在自译解[`project_self_analysis.md`](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)详细说明。随着版本的迭代,您也可以随时自行点击相关函数插件,调用GPT重新生成项目的自我解析报告。常见问题汇总在[`wiki`](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98)当中。
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> 2.本项目中每个文件的功能都在自译解[`self_analysis.md`](https://github.com/binary-husky/chatgpt_academic/wiki/chatgpt-academic%E9%A1%B9%E7%9B%AE%E8%87%AA%E8%AF%91%E8%A7%A3%E6%8A%A5%E5%91%8A)详细说明。随着版本的迭代,您也可以随时自行点击相关函数插件,调用GPT重新生成项目的自我解析报告。常见问题汇总在[`wiki`](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%B8%B8%E8%A7%81%E9%97%AE%E9%A2%98)当中。
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>
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> 3.如果您不太习惯部分中文命名的函数,您可以随时点击相关函数插件,调用GPT一键生成纯英文的项目源代码。
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> 3.如果您不太习惯部分中文命名的函数、注释或者界面,您可以随时点击相关函数插件,调用ChatGPT一键生成纯英文的项目源代码。
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<div align="center">
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@@ -35,17 +35,17 @@ https://github.com/polarwinkel/mdtex2html
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一键代码解释 | 可以正确显示代码、解释代码
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自定义快捷键 | 支持自定义快捷键
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配置代理服务器 | 支持配置代理服务器
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模块化设计 | 支持自定义高阶的实验性功能
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模块化设计 | 支持自定义高阶的实验性功能与[函数插件],插件支持[热更新](https://github.com/binary-husky/chatgpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
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自我程序剖析 | [函数插件] 一键读懂本项目的源代码
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程序剖析 | [函数插件] 一键可以剖析其他Python/C++等项目
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程序剖析 | [函数插件] 一键可以剖析其他Python/C/C++/Java项目树
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读论文 | [函数插件] 一键解读latex论文全文并生成摘要
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arxiv小助手 | [函数插件] 输入url一键翻译摘要+下载论文
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批量注释生成 | [函数插件] 一键批量生成函数注释
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chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
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arxiv小助手 | [函数插件] 输入arxiv文章url即可一键翻译摘要+下载PDF
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公式显示 | 可以同时显示公式的tex形式和渲染形式
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图片显示 | 可以在markdown中显示图片
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多线程函数插件支持 | 支持多线调用chatgpt,一键处理海量文本或程序
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支持GPT输出的markdown表格 | 可以输出支持GPT的markdown表格
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本地大语言模型接口 | 借助[TGUI](https://github.com/oobabooga/text-generation-webui)接入galactica等本地语言模型
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…… | ……
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</div>
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@@ -194,7 +194,7 @@ input区域 输入 ./crazy_functions/test_project/python/dqn , 然后点击 "[
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如果你发明了更好用的学术快捷键,欢迎发issue或者pull requests!
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## 配置代理
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### 方法一:常规方法
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在```config.py```中修改端口与代理软件对应
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<div align="center">
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@@ -206,6 +206,8 @@ input区域 输入 ./crazy_functions/test_project/python/dqn , 然后点击 "[
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```
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python check_proxy.py
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```
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### 方法二:纯新手教程
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[纯新手教程](https://github.com/binary-husky/chatgpt_academic/wiki/%E4%BB%A3%E7%90%86%E8%BD%AF%E4%BB%B6%E9%97%AE%E9%A2%98%E7%9A%84%E6%96%B0%E6%89%8B%E8%A7%A3%E5%86%B3%E6%96%B9%E6%B3%95%EF%BC%88%E6%96%B9%E6%B3%95%E5%8F%AA%E9%80%82%E7%94%A8%E4%BA%8E%E6%96%B0%E6%89%8B%EF%BC%89)
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## 兼容性测试
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@@ -249,7 +251,7 @@ python check_proxy.py
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### 模块化功能设计
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<div align="center">
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<img src="https://user-images.githubusercontent.com/96192199/227504981-4c6c39c0-ae79-47e6-bffe-0e6442d9da65.png" height="400" >
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<img src="https://user-images.githubusercontent.com/96192199/229288270-093643c1-0018-487a-81e6-1d7809b6e90f.png" height="400" >
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<img src="https://user-images.githubusercontent.com/96192199/227504931-19955f78-45cd-4d1c-adac-e71e50957915.png" height="400" >
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</div>
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@@ -257,5 +259,5 @@ python check_proxy.py
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- (Top Priority) 调用另一个开源项目text-generation-webui的web接口,使用其他llm模型
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- 总结大工程源代码时,文本过长、token溢出的问题(目前的方法是直接二分丢弃处理溢出,过于粗暴,有效信息大量丢失)
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- UI不够美观
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@@ -0,0 +1,150 @@
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import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
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import gradio as gr
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from predict import predict
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from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf
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# 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
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proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT = \
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get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT')
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# 如果WEB_PORT是-1, 则随机选取WEB端口
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PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
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if not AUTHENTICATION: AUTHENTICATION = None
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initial_prompt = "Serve me as a writing and programming assistant."
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title_html = "<h1 align=\"center\">ChatGPT 学术优化</h1>"
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description = """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic),感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
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# 问询记录, python 版本建议3.9+(越新越好)
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import logging
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os.makedirs("gpt_log", exist_ok=True)
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try:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, encoding="utf-8")
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except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO)
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print("所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log, 请注意自我隐私保护哦!")
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# 一些普通功能模块
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from functional import get_functionals
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functional = get_functionals()
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# 高级函数插件
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from functional_crazy import get_crazy_functionals
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crazy_fns = get_crazy_functionals()
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# 处理markdown文本格式的转变
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gr.Chatbot.postprocess = format_io
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# 做一些外观色彩上的调整
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from theme import adjust_theme, advanced_css
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set_theme = adjust_theme()
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cancel_handles = []
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with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
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gr.HTML(title_html)
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# To add a Duplicate Space badge
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gr.HTML('''<center><a href="https://huggingface.co/spaces/qingxu98/gpt-academic?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>请您打开此页面后务必点击上方的“复制空间”(Duplicate Space)按钮!<br/>切忌在“复制空间”(Duplicate Space)之前填入API_KEY或进行提问,否则您的API_KEY将极可能被空间所有者攫取!</center>''')
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with gr.Row().style(equal_height=True):
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with gr.Column(scale=2):
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chatbot = gr.Chatbot()
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chatbot.style(height=CHATBOT_HEIGHT)
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history = gr.State([])
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with gr.Column(scale=1):
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with gr.Row():
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api_key = gr.Textbox(show_label=False, placeholder="输入API_KEY,输入后自动生效.").style(container=False)
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with gr.Row():
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txt = gr.Textbox(show_label=False, placeholder="输入问题.").style(container=False)
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with gr.Row():
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submitBtn = gr.Button("提交", variant="primary")
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with gr.Row():
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resetBtn = gr.Button("重置", variant="secondary"); resetBtn.style(size="sm")
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stopBtn = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
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with gr.Row():
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from check_proxy import check_proxy
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status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {check_proxy(proxies)}")
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with gr.Accordion("基础功能区", open=True) as area_basic_fn:
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with gr.Row():
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for k in functional:
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variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
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functional[k]["Button"] = gr.Button(k, variant=variant)
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with gr.Accordion("函数插件区", open=True) as area_crazy_fn:
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with gr.Row():
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gr.Markdown("注意:以下“红颜色”标识的函数插件需从input区读取路径作为参数.")
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with gr.Row():
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for k in crazy_fns:
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if not crazy_fns[k].get("AsButton", True): continue
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variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
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crazy_fns[k]["Button"] = gr.Button(k, variant=variant)
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with gr.Row():
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with gr.Accordion("更多函数插件", open=True):
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dropdown_fn_list = [k for k in crazy_fns.keys() if not crazy_fns[k].get("AsButton", True)]
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with gr.Column(scale=1):
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dropdown = gr.Dropdown(dropdown_fn_list, value=r"打开插件列表", label="").style(container=False)
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with gr.Column(scale=1):
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switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary")
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with gr.Row():
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with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", open=False) as area_file_up:
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file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
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with gr.Accordion("展开SysPrompt & 交互界面布局 & Github地址", open=False):
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system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
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top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
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temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
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checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
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gr.Markdown(description)
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# 功能区显示开关与功能区的互动
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def fn_area_visibility(a):
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ret = {}
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ret.update({area_basic_fn: gr.update(visible=("基础功能区" in a))})
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ret.update({area_crazy_fn: gr.update(visible=("函数插件区" in a))})
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return ret
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checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn] )
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# 整理反复出现的控件句柄组合
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input_combo = [txt, top_p, api_key, temperature, chatbot, history, system_prompt]
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output_combo = [chatbot, history, status]
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predict_args = dict(fn=predict, inputs=input_combo, outputs=output_combo)
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empty_txt_args = dict(fn=lambda: "", inputs=[], outputs=[txt]) # 用于在提交后清空输入栏
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# 提交按钮、重置按钮
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cancel_handles.append(txt.submit(**predict_args)) #; txt.submit(**empty_txt_args) 在提交后清空输入栏
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cancel_handles.append(submitBtn.click(**predict_args)) #; submitBtn.click(**empty_txt_args) 在提交后清空输入栏
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resetBtn.click(lambda: ([], [], "已重置"), None, output_combo)
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# 基础功能区的回调函数注册
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for k in functional:
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click_handle = functional[k]["Button"].click(predict, [*input_combo, gr.State(True), gr.State(k)], output_combo)
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cancel_handles.append(click_handle)
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# 文件上传区,接收文件后与chatbot的互动
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file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt], [chatbot, txt])
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# 函数插件-固定按钮区
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for k in crazy_fns:
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if not crazy_fns[k].get("AsButton", True): continue
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click_handle = crazy_fns[k]["Button"].click(crazy_fns[k]["Function"], [*input_combo, gr.State(PORT)], output_combo)
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click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
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cancel_handles.append(click_handle)
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# 函数插件-下拉菜单与随变按钮的互动
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def on_dropdown_changed(k):
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variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
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return {switchy_bt: gr.update(value=k, variant=variant)}
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dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt] )
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# 随变按钮的回调函数注册
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def route(k, *args, **kwargs):
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if k in [r"打开插件列表", r"请先从插件列表中选择"]: return
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yield from crazy_fns[k]["Function"](*args, **kwargs)
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click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
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click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
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# def expand_file_area(file_upload, area_file_up):
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# if len(file_upload)>0: return {area_file_up: gr.update(open=True)}
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# click_handle.then(expand_file_area, [file_upload, area_file_up], [area_file_up])
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cancel_handles.append(click_handle)
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# 终止按钮的回调函数注册
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stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
|
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|
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# gradio的inbrowser触发不太稳定,回滚代码到原始的浏览器打开函数
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def auto_opentab_delay():
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import threading, webbrowser, time
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print(f"如果浏览器没有自动打开,请复制并转到以下URL: http://localhost:{PORT}")
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def open():
|
||||
time.sleep(2)
|
||||
webbrowser.open_new_tab(f"http://localhost:{PORT}")
|
||||
threading.Thread(target=open, name="open-browser", daemon=True).start()
|
||||
|
||||
auto_opentab_delay()
|
||||
demo.title = "ChatGPT 学术优化"
|
||||
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=False)
|
||||
@@ -1,5 +1,5 @@
|
||||
# [step 1]>> 例如: API_KEY = "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" (此key无效)
|
||||
API_KEY = "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"
|
||||
API_KEY = "sk-此处填API密钥"
|
||||
|
||||
# [step 2]>> 改为True应用代理,如果直接在海外服务器部署,此处不修改
|
||||
USE_PROXY = False
|
||||
@@ -22,19 +22,19 @@ else:
|
||||
|
||||
# [step 3]>> 以下配置可以优化体验,但大部分场合下并不需要修改
|
||||
# 对话窗的高度
|
||||
CHATBOT_HEIGHT = 1116
|
||||
CHATBOT_HEIGHT = 1115
|
||||
|
||||
# 发送请求到OpenAI后,等待多久判定为超时
|
||||
TIMEOUT_SECONDS = 25
|
||||
|
||||
# 网页的端口, -1代表随机端口
|
||||
WEB_PORT = -1
|
||||
WEB_PORT = 7860
|
||||
|
||||
# 如果OpenAI不响应(网络卡顿、代理失败、KEY失效),重试的次数限制
|
||||
MAX_RETRY = 2
|
||||
|
||||
# OpenAI模型选择是(gpt4现在只对申请成功的人开放)
|
||||
LLM_MODEL = "TGUI:galactica-1.3b@localhost:7860" # "gpt-3.5-turbo"
|
||||
LLM_MODEL = "gpt-3.5-turbo"
|
||||
|
||||
# OpenAI的API_URL
|
||||
API_URL = "https://api.openai.com/v1/chat/completions"
|
||||
@@ -42,5 +42,5 @@ API_URL = "https://api.openai.com/v1/chat/completions"
|
||||
# 设置并行使用的线程数
|
||||
CONCURRENT_COUNT = 100
|
||||
|
||||
# 设置用户名和密码
|
||||
# 设置用户名和密码(相关功能不稳定,与gradio版本和网络都相关,如果本地使用不建议加这个)
|
||||
AUTHENTICATION = [] # [("username", "password"), ("username2", "password2"), ...]
|
||||
|
||||
@@ -132,10 +132,9 @@ def get_name(_url_):
|
||||
|
||||
|
||||
@CatchException
|
||||
def 下载arxiv论文并翻译摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 下载arxiv论文并翻译摘要(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
|
||||
CRAZY_FUNCTION_INFO = "下载arxiv论文并翻译摘要,作者 binary-husky。正在提取摘要并下载PDF文档……"
|
||||
raise RuntimeError()
|
||||
CRAZY_FUNCTION_INFO = "下载arxiv论文并翻译摘要,函数插件作者[binary-husky]。正在提取摘要并下载PDF文档……"
|
||||
import glob
|
||||
import os
|
||||
|
||||
@@ -173,15 +172,15 @@ def 下载arxiv论文并翻译摘要(txt, top_p, temperature, chatbot, history,
|
||||
yield chatbot, history, '正常'
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
history.append(i_say_show_user); history.append(gpt_say)
|
||||
yield chatbot, history, msg
|
||||
# 写入文件
|
||||
import shutil
|
||||
# 重置文件的创建时间
|
||||
shutil.copyfile(pdf_path, pdf_path.replace('.pdf', '.autodownload.pdf')); os.remove(pdf_path)
|
||||
shutil.copyfile(pdf_path, f'./gpt_log/{os.path.basename(pdf_path)}'); os.remove(pdf_path)
|
||||
res = write_results_to_file(history)
|
||||
chatbot.append(("完成了吗?", res))
|
||||
chatbot.append(("完成了吗?", res + "\n\nPDF文件也已经下载"))
|
||||
yield chatbot, history, msg
|
||||
|
||||
|
||||
@@ -5,7 +5,7 @@ from toolbox import CatchException, write_results_to_file
|
||||
|
||||
|
||||
@CatchException
|
||||
def 全项目切换英文(txt, top_p, temperature, chatbot, history, sys_prompt, WEB_PORT):
|
||||
def 全项目切换英文(txt, top_p, api_key, temperature, chatbot, history, sys_prompt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
# 集合文件
|
||||
import time, glob, os
|
||||
@@ -32,7 +32,7 @@ def 全项目切换英文(txt, top_p, temperature, chatbot, history, sys_prompt,
|
||||
file_content = f.read()
|
||||
i_say = f'接下来请将以下代码中包含的所有中文转化为英文,只输出代码,文件名是{fp},文件代码是 ```{file_content}```'
|
||||
# ** gpt request **
|
||||
gpt_say = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
gpt_say = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
mutable_return[index] = gpt_say
|
||||
|
||||
# 所有线程同时开始执行任务函数
|
||||
|
||||
@@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
|
||||
fast_debug = False
|
||||
|
||||
|
||||
def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, os
|
||||
# pip install python-docx 用于docx格式,跨平台
|
||||
# pip install pywin32 用于doc格式,仅支持Win平台
|
||||
@@ -40,7 +40,7 @@ def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, histo
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature,
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature,
|
||||
history=[]) # 带超时倒计时
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
history.append(i_say_show_user);
|
||||
@@ -66,7 +66,7 @@ def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, histo
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature,
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature,
|
||||
history=history) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
@@ -79,7 +79,7 @@ def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, histo
|
||||
|
||||
|
||||
@CatchException
|
||||
def 总结word文档(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 总结word文档(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
import glob, os
|
||||
|
||||
# 基本信息:功能、贡献者
|
||||
@@ -124,4 +124,4 @@ def 总结word文档(txt, top_p, temperature, chatbot, history, systemPromptTxt,
|
||||
return
|
||||
|
||||
# 开始正式执行任务
|
||||
yield from 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@@ -57,7 +57,7 @@ def clean_text(raw_text):
|
||||
|
||||
return final_text.strip()
|
||||
|
||||
def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, glob, os, fitz
|
||||
print('begin analysis on:', file_manifest)
|
||||
for index, fp in enumerate(file_manifest):
|
||||
@@ -78,7 +78,7 @@ def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, histor
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
print('[2] end gpt req')
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
@@ -96,7 +96,7 @@ def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, histor
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@@ -107,7 +107,7 @@ def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, histor
|
||||
|
||||
|
||||
@CatchException
|
||||
def 批量总结PDF文档(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 批量总结PDF文档(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
import glob, os
|
||||
|
||||
# 基本信息:功能、贡献者
|
||||
@@ -151,4 +151,4 @@ def 批量总结PDF文档(txt, top_p, temperature, chatbot, history, systemPromp
|
||||
return
|
||||
|
||||
# 开始正式执行任务
|
||||
yield from 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@@ -61,7 +61,7 @@ def readPdf(pdfPath):
|
||||
return outTextList
|
||||
|
||||
|
||||
def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, glob, os
|
||||
from bs4 import BeautifulSoup
|
||||
print('begin analysis on:', file_manifest)
|
||||
@@ -83,7 +83,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
print('[2] end gpt req')
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
@@ -101,7 +101,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@@ -113,7 +113,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
|
||||
|
||||
@CatchException
|
||||
def 批量总结PDF文档pdfminer(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 批量总结PDF文档pdfminer(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
|
||||
@@ -147,5 +147,5 @@ def 批量总结PDF文档pdfminer(txt, top_p, temperature, chatbot, history, sys
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或pdf文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
|
||||
fast_debug = False
|
||||
|
||||
|
||||
def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 生成函数注释(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, glob, os
|
||||
print('begin analysis on:', file_manifest)
|
||||
for index, fp in enumerate(file_manifest):
|
||||
@@ -19,7 +19,7 @@ def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbo
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
print('[2] end gpt req')
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
@@ -37,7 +37,7 @@ def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbo
|
||||
|
||||
|
||||
@CatchException
|
||||
def 批量生成函数注释(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 批量生成函数注释(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@@ -54,4 +54,4 @@ def 批量生成函数注释(txt, top_p, temperature, chatbot, history, systemPr
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 生成函数注释(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
+65
-19
@@ -2,7 +2,7 @@ from predict import predict_no_ui
|
||||
from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down
|
||||
fast_debug = False
|
||||
|
||||
def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, glob, os
|
||||
print('begin analysis on:', file_manifest)
|
||||
for index, fp in enumerate(file_manifest):
|
||||
@@ -19,7 +19,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
|
||||
msg = '正常'
|
||||
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
history.append(i_say_show_user); history.append(gpt_say)
|
||||
@@ -34,7 +34,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@@ -47,7 +47,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析项目本身(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import time, glob, os
|
||||
file_manifest = [f for f in glob.glob('./*.py') if ('test_project' not in f) and ('gpt_log' not in f)] + \
|
||||
@@ -65,8 +65,8 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
|
||||
|
||||
if not fast_debug:
|
||||
# ** gpt request **
|
||||
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature)
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], long_connection=True) # 带超时倒计时
|
||||
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature)
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[], long_connection=True) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
history.append(i_say_show_user); history.append(gpt_say)
|
||||
@@ -79,8 +79,8 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
|
||||
|
||||
if not fast_debug:
|
||||
# ** gpt request **
|
||||
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history)
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history, long_connection=True) # 带超时倒计时
|
||||
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history)
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history, long_connection=True) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@@ -90,7 +90,7 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
|
||||
yield chatbot, history, '正常'
|
||||
|
||||
@CatchException
|
||||
def 解析一个Python项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个Python项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@@ -105,11 +105,11 @@ def 解析一个Python项目(txt, top_p, temperature, chatbot, history, systemPr
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何python文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个C项目的头文件(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@@ -126,10 +126,10 @@ def 解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, s
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@CatchException
|
||||
def 解析一个C项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@@ -146,22 +146,68 @@ def 解析一个C项目(txt, top_p, temperature, chatbot, history, systemPromptT
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个Golang项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
def 解析一个Java项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, 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"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.java', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.jar', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.xml', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.sh', recursive=True)]
|
||||
if len(file_manifest) == 0:
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何java文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个Rect项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, 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"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.ts', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.tsx', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.json', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.js', recursive=True)] + \
|
||||
[f for f in glob.glob(f'{project_folder}/**/*.jsx', recursive=True)]
|
||||
if len(file_manifest) == 0:
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何Rect文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个Golang项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, 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"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.go', recursive=True)]
|
||||
if len(file_manifest) == 0:
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何golang文件: {txt}")
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何golang文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
|
||||
fast_debug = False
|
||||
|
||||
|
||||
def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, glob, os
|
||||
print('begin analysis on:', file_manifest)
|
||||
for index, fp in enumerate(file_manifest):
|
||||
@@ -20,7 +20,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
print('[2] end gpt req')
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
@@ -38,7 +38,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@@ -50,7 +50,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
|
||||
|
||||
@CatchException
|
||||
def 读文章写摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 读文章写摘要(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@@ -67,4 +67,4 @@ def 读文章写摘要(txt, top_p, temperature, chatbot, history, systemPromptTx
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file
|
||||
import datetime
|
||||
|
||||
@CatchException
|
||||
def 高阶功能模板函数(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 高阶功能模板函数(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史,以免输入溢出
|
||||
chatbot.append(("这是什么功能?", "[Local Message] 请注意,您正在调用一个[函数插件]的模板,该函数面向希望实现更多有趣功能的开发者,它可以作为创建新功能函数的模板。为了做到简单易读,该函数只有25行代码,所以不会实时反馈文字流或心跳,请耐心等待程序输出完成。此外我们也提供可同步处理大量文件的多线程Demo供您参考。您若希望分享新的功能模组,请不吝PR!"))
|
||||
yield chatbot, history, '正常' # 由于请求gpt需要一段时间,我们先及时地做一次状态显示
|
||||
@@ -17,7 +17,7 @@ def 高阶功能模板函数(txt, top_p, temperature, chatbot, history, systemPr
|
||||
|
||||
# history = [] 每次询问不携带之前的询问历史
|
||||
gpt_say = predict_no_ui_long_connection(
|
||||
inputs=i_say, top_p=top_p, temperature=temperature, history=[],
|
||||
inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=[],
|
||||
sys_prompt="当你想发送一张照片时,请使用Markdown, 并且不要有反斜线, 不要用代码块。使用 Unsplash API (https://source.unsplash.com/1280x720/? < PUT_YOUR_QUERY_HERE >)。") # 请求gpt,需要一段时间
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
|
||||
+45
-27
@@ -1,13 +1,8 @@
|
||||
from toolbox import HotReload # HotReload 的意思是热更新,修改函数插件后,不需要重启程序,代码直接生效
|
||||
|
||||
# UserVisibleLevel是过滤器参数。
|
||||
# 由于UI界面空间有限,所以通过这种方式决定UI界面中显示哪些插件
|
||||
# 默认函数插件 VisibleLevel 是 0
|
||||
# 当 UserVisibleLevel >= 函数插件的 VisibleLevel 时,该函数插件才会被显示出来
|
||||
UserVisibleLevel = 1
|
||||
|
||||
|
||||
def get_crazy_functionals():
|
||||
###################### 第一组插件 ###########################
|
||||
# [第一组插件]: 最早期编写的项目插件和一些demo
|
||||
from crazy_functions.读文章写摘要 import 读文章写摘要
|
||||
from crazy_functions.生成函数注释 import 批量生成函数注释
|
||||
from crazy_functions.解析项目源代码 import 解析项目本身
|
||||
@@ -15,6 +10,8 @@ def get_crazy_functionals():
|
||||
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
|
||||
from crazy_functions.解析项目源代码 import 解析一个Java项目
|
||||
from crazy_functions.解析项目源代码 import 解析一个Rect项目
|
||||
from crazy_functions.高级功能函数模板 import 高阶功能模板函数
|
||||
from crazy_functions.代码重写为全英文_多线程 import 全项目切换英文
|
||||
|
||||
@@ -41,6 +38,16 @@ def get_crazy_functionals():
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": 解析一个Golang项目
|
||||
},
|
||||
"解析整个Java项目": {
|
||||
"Color": "stop", # 按钮颜色
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": 解析一个Java项目
|
||||
},
|
||||
"解析整个Java项目": {
|
||||
"Color": "stop", # 按钮颜色
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": 解析一个Rect项目
|
||||
},
|
||||
"读Tex论文写摘要": {
|
||||
"Color": "stop", # 按钮颜色
|
||||
"Function": 读文章写摘要
|
||||
@@ -58,33 +65,44 @@ def get_crazy_functionals():
|
||||
"Function": HotReload(高阶功能模板函数)
|
||||
},
|
||||
}
|
||||
###################### 第二组插件 ###########################
|
||||
# [第二组插件]: 经过充分测试,但功能上距离达到完美状态还差一点点
|
||||
from crazy_functions.批量总结PDF文档 import 批量总结PDF文档
|
||||
from crazy_functions.批量总结PDF文档pdfminer import 批量总结PDF文档pdfminer
|
||||
from crazy_functions.总结word文档 import 总结word文档
|
||||
function_plugins.update({
|
||||
"[仅供开发调试] 批量总结PDF文档": {
|
||||
"Color": "stop",
|
||||
"Function": HotReload(批量总结PDF文档) # HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
},
|
||||
"[仅供开发调试] 批量总结PDF文档pdfminer": {
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(批量总结PDF文档pdfminer)
|
||||
},
|
||||
"[仅供开发调试] 批量总结Word文档": {
|
||||
"Color": "stop",
|
||||
"Function": HotReload(总结word文档)
|
||||
},
|
||||
})
|
||||
|
||||
# VisibleLevel=1 经过测试,但功能上距离达到完美状态还差一点点
|
||||
if UserVisibleLevel >= 1:
|
||||
from crazy_functions.批量总结PDF文档 import 批量总结PDF文档
|
||||
from crazy_functions.批量总结PDF文档pdfminer import 批量总结PDF文档pdfminer
|
||||
from crazy_functions.总结word文档 import 总结word文档
|
||||
###################### 第三组插件 ###########################
|
||||
# [第三组插件]: 尚未充分测试的函数插件,放在这里
|
||||
try:
|
||||
from crazy_functions.下载arxiv论文翻译摘要 import 下载arxiv论文并翻译摘要
|
||||
function_plugins.update({
|
||||
"[仅供开发调试] 批量总结PDF文档": {
|
||||
"Color": "stop",
|
||||
"Function": HotReload(批量总结PDF文档) # HotReload 的意思是热更新,修改函数插件代码后,不需要重启程序,代码直接生效
|
||||
},
|
||||
"[仅供开发调试] 批量总结PDF文档pdfminer": {
|
||||
"一键下载arxiv论文并翻译摘要(先在input输入编号,如1812.10695)": {
|
||||
"Color": "stop",
|
||||
"AsButton": False, # 加入下拉菜单中
|
||||
"Function": HotReload(批量总结PDF文档pdfminer)
|
||||
},
|
||||
"[仅供开发调试] 批量总结Word文档": {
|
||||
"Color": "stop",
|
||||
"Function": HotReload(总结word文档)
|
||||
},
|
||||
"Function": HotReload(下载arxiv论文并翻译摘要)
|
||||
}
|
||||
})
|
||||
except Exception as err:
|
||||
print(f'[下载arxiv论文并翻译摘要] 插件导入失败 {str(err)}')
|
||||
|
||||
# VisibleLevel=2 尚未充分测试的函数插件,放在这里
|
||||
if UserVisibleLevel >= 2:
|
||||
function_plugins.update({
|
||||
})
|
||||
|
||||
|
||||
###################### 第n组插件 ###########################
|
||||
return function_plugins
|
||||
|
||||
|
||||
|
||||
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|
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|
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|
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@@ -1,3 +1,4 @@
|
||||
assert False, "Huggingface版请运行app.py"
|
||||
import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
|
||||
import gradio as gr
|
||||
from predict import predict
|
||||
@@ -11,9 +12,9 @@ proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT =
|
||||
PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
|
||||
if not AUTHENTICATION: AUTHENTICATION = None
|
||||
|
||||
title = "ChatGPT 学术优化" if LLM_MODEL.startswith('gpt') else "ChatGPT / LLM 学术优化"
|
||||
initial_prompt = "Serve me as a writing and programming assistant."
|
||||
title_html = f"<h1 align=\"center\">{title}</h1>"
|
||||
title_html = "<h1 align=\"center\">ChatGPT 学术优化</h1>"
|
||||
description = """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic),感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
|
||||
|
||||
# 问询记录, python 版本建议3.9+(越新越好)
|
||||
import logging
|
||||
@@ -40,6 +41,9 @@ set_theme = adjust_theme()
|
||||
cancel_handles = []
|
||||
with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
|
||||
gr.HTML(title_html)
|
||||
# To add a Duplicate Space badge
|
||||
gr.HTML('''<center><a href="https://huggingface.co/spaces/qingxu98/gpt-academic?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>请您打开此页面后务必点击上方的“复制空间”(Duplicate Space)按钮!<br/>切忌在“复制空间”(Duplicate Space)之前填入API_KEY或进行提问,否则您的API_KEY将极可能被空间所有者攫取!</center>''')
|
||||
|
||||
with gr.Row().style(equal_height=True):
|
||||
with gr.Column(scale=2):
|
||||
chatbot = gr.Chatbot()
|
||||
@@ -47,7 +51,9 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
|
||||
history = gr.State([])
|
||||
with gr.Column(scale=1):
|
||||
with gr.Row():
|
||||
txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
|
||||
api_key = gr.Textbox(show_label=False, placeholder="输入API_KEY,输入后自动生效.").style(container=False)
|
||||
with gr.Row():
|
||||
txt = gr.Textbox(show_label=False, placeholder="输入问题.").style(container=False)
|
||||
with gr.Row():
|
||||
submitBtn = gr.Button("提交", variant="primary")
|
||||
with gr.Row():
|
||||
@@ -79,12 +85,12 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
|
||||
with gr.Row():
|
||||
with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", 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("展开SysPrompt & GPT参数 & 交互界面布局", open=False):
|
||||
with gr.Accordion("展开SysPrompt & 交互界面布局 & Github地址", open=False):
|
||||
system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
|
||||
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",)
|
||||
checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
|
||||
|
||||
gr.Markdown(description)
|
||||
# 功能区显示开关与功能区的互动
|
||||
def fn_area_visibility(a):
|
||||
ret = {}
|
||||
@@ -93,7 +99,7 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
|
||||
return ret
|
||||
checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn] )
|
||||
# 整理反复出现的控件句柄组合
|
||||
input_combo = [txt, top_p, temperature, chatbot, history, system_prompt]
|
||||
input_combo = [txt, top_p, api_key, temperature, chatbot, history, system_prompt]
|
||||
output_combo = [chatbot, history, status]
|
||||
predict_args = dict(fn=predict, inputs=input_combo, outputs=output_combo)
|
||||
empty_txt_args = dict(fn=lambda: "", inputs=[], outputs=[txt]) # 用于在提交后清空输入栏
|
||||
@@ -120,7 +126,7 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
|
||||
dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt] )
|
||||
# 随变按钮的回调函数注册
|
||||
def route(k, *args, **kwargs):
|
||||
if k in [r"打开插件列表", r"先从插件列表中选择"]: return
|
||||
if k in [r"打开插件列表", r"请先从插件列表中选择"]: return
|
||||
yield from crazy_fns[k]["Function"](*args, **kwargs)
|
||||
click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
|
||||
click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
|
||||
@@ -141,5 +147,5 @@ def auto_opentab_delay():
|
||||
threading.Thread(target=open, name="open-browser", daemon=True).start()
|
||||
|
||||
auto_opentab_delay()
|
||||
demo.title = title
|
||||
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=True, server_port=PORT, auth=AUTHENTICATION)
|
||||
demo.title = "ChatGPT 学术优化"
|
||||
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=False)
|
||||
|
||||
+17
-22
@@ -38,18 +38,18 @@ def get_full_error(chunk, stream_response):
|
||||
break
|
||||
return chunk
|
||||
|
||||
def predict_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
|
||||
def predict_no_ui(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
|
||||
"""
|
||||
发送至chatGPT,等待回复,一次性完成,不显示中间过程。
|
||||
predict函数的简化版。
|
||||
用于payload比较大的情况,或者用于实现多线、带嵌套的复杂功能。
|
||||
|
||||
inputs 是本次问询的输入
|
||||
top_p, temperature是chatGPT的内部调优参数
|
||||
top_p, api_key, temperature是chatGPT的内部调优参数
|
||||
history 是之前的对话列表
|
||||
(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误,然后raise ConnectionAbortedError)
|
||||
"""
|
||||
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=False)
|
||||
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt=sys_prompt, stream=False)
|
||||
|
||||
retry = 0
|
||||
while True:
|
||||
@@ -71,11 +71,11 @@ def predict_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
|
||||
raise ConnectionAbortedError("Json解析不合常规,可能是文本过长" + response.text)
|
||||
|
||||
|
||||
def predict_no_ui_long_connection(inputs, top_p, temperature, history=[], sys_prompt=""):
|
||||
def predict_no_ui_long_connection(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
|
||||
"""
|
||||
发送至chatGPT,等待回复,一次性完成,不显示中间过程。但内部用stream的方法避免有人中途掐网线。
|
||||
"""
|
||||
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=True)
|
||||
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt=sys_prompt, stream=True)
|
||||
|
||||
retry = 0
|
||||
while True:
|
||||
@@ -112,12 +112,13 @@ def predict_no_ui_long_connection(inputs, top_p, temperature, history=[], sys_pr
|
||||
return result
|
||||
|
||||
|
||||
def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None):
|
||||
def predict(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_prompt='',
|
||||
stream = True, additional_fn=None):
|
||||
"""
|
||||
发送至chatGPT,流式获取输出。
|
||||
用于基础的对话功能。
|
||||
inputs 是本次问询的输入
|
||||
top_p, temperature是chatGPT的内部调优参数
|
||||
top_p, api_key, temperature是chatGPT的内部调优参数
|
||||
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
||||
chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||
@@ -135,7 +136,7 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
|
||||
chatbot.append((inputs, ""))
|
||||
yield chatbot, history, "等待响应"
|
||||
|
||||
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
|
||||
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt, stream)
|
||||
history.append(inputs); history.append(" ")
|
||||
|
||||
retry = 0
|
||||
@@ -185,23 +186,25 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
|
||||
error_msg = chunk.decode()
|
||||
if "reduce the length" in error_msg:
|
||||
chatbot[-1] = (chatbot[-1][0], "[Local Message] Input (or history) is too long, please reduce input or clear history by refreshing this page.")
|
||||
history = []
|
||||
history = [] # 清除历史
|
||||
elif "Incorrect API key" in error_msg:
|
||||
chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key provided.")
|
||||
elif "exceeded your current quota" in error_msg:
|
||||
chatbot[-1] = (chatbot[-1][0], "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由,拒绝服务.")
|
||||
else:
|
||||
from toolbox import regular_txt_to_markdown
|
||||
tb_str = regular_txt_to_markdown(traceback.format_exc())
|
||||
chatbot[-1] = (chatbot[-1][0], f"[Local Message] Json Error \n\n {tb_str} \n\n {regular_txt_to_markdown(chunk.decode()[4:])}")
|
||||
yield chatbot, history, "Json解析不合常规" + error_msg
|
||||
tb_str = '```\n' + traceback.format_exc() + '```'
|
||||
chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk.decode()[4:])}")
|
||||
yield chatbot, history, "Json异常" + error_msg
|
||||
return
|
||||
|
||||
def generate_payload(inputs, top_p, temperature, history, system_prompt, stream):
|
||||
def generate_payload(inputs, top_p, api_key, temperature, history, system_prompt, stream):
|
||||
"""
|
||||
整合所有信息,选择LLM模型,生成http请求,为发送请求做准备
|
||||
"""
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {API_KEY}"
|
||||
"Authorization": f"Bearer {api_key}"
|
||||
}
|
||||
|
||||
conversation_cnt = len(history) // 2
|
||||
@@ -243,11 +246,3 @@ def generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
|
||||
return headers,payload
|
||||
|
||||
|
||||
if not LLM_MODEL.startswith('gpt'):
|
||||
# 函数重载到另一个文件
|
||||
from request_llm.bridge_tgui import predict_tgui, predict_tgui_no_ui
|
||||
predict = predict_tgui
|
||||
predict_no_ui = predict_tgui_no_ui
|
||||
predict_no_ui_long_connection = predict_tgui_no_ui
|
||||
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
# 如何使用其他大语言模型
|
||||
# 如何使用其他大语言模型(dev分支测试中)
|
||||
|
||||
## 1. 先运行text-generation
|
||||
``` sh
|
||||
|
||||
@@ -90,12 +90,12 @@ async def run(context, max_token=512):
|
||||
|
||||
|
||||
|
||||
def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None):
|
||||
def predict_tgui(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None):
|
||||
"""
|
||||
发送至chatGPT,流式获取输出。
|
||||
用于基础的对话功能。
|
||||
inputs 是本次问询的输入
|
||||
top_p, temperature是chatGPT的内部调优参数
|
||||
top_p, api_key, temperature是chatGPT的内部调优参数
|
||||
history 是之前的对话列表(注意无论是inputs还是history,内容太长了都会触发token数量溢出的错误)
|
||||
chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
||||
additional_fn代表点击的哪个按钮,按钮见functional.py
|
||||
@@ -144,7 +144,7 @@ def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prom
|
||||
|
||||
|
||||
|
||||
def predict_tgui_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
|
||||
def predict_tgui_no_ui(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
|
||||
raw_input = "What I would like to say is the following: " + inputs
|
||||
prompt = inputs
|
||||
tgui_say = ""
|
||||
|
||||
@@ -3,3 +3,7 @@ requests[socks]
|
||||
mdtex2html
|
||||
Markdown
|
||||
latex2mathml
|
||||
pdfminer
|
||||
beautifulsoup4
|
||||
rarfile
|
||||
py7zr
|
||||
+5
-5
@@ -131,11 +131,11 @@
|
||||
|
||||
这个程序文件中包含了几个函数,分别是:
|
||||
|
||||
1. `解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)`:通过输入文件路径列表对程序文件进行逐文件分析,根据分析结果做出整体功能和构架的概括,并生成包括每个文件功能的markdown表格。
|
||||
2. `解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对当前文件夹下的所有Python文件及其子文件夹进行逐文件分析,并生成markdown表格。
|
||||
3. `解析一个Python项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有Python文件及其子文件夹进行逐文件分析,并生成markdown表格。
|
||||
4. `解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有头文件进行逐文件分析,并生成markdown表格。
|
||||
5. `解析一个C项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有.h、.cpp、.c文件及其子文件夹进行逐文件分析,并生成markdown表格。
|
||||
1. `解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)`:通过输入文件路径列表对程序文件进行逐文件分析,根据分析结果做出整体功能和构架的概括,并生成包括每个文件功能的markdown表格。
|
||||
2. `解析项目本身(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对当前文件夹下的所有Python文件及其子文件夹进行逐文件分析,并生成markdown表格。
|
||||
3. `解析一个Python项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有Python文件及其子文件夹进行逐文件分析,并生成markdown表格。
|
||||
4. `解析一个C项目的头文件(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有头文件进行逐文件分析,并生成markdown表格。
|
||||
5. `解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`:对指定路径下的所有.h、.cpp、.c文件及其子文件夹进行逐文件分析,并生成markdown表格。
|
||||
|
||||
程序中还包含了一些辅助函数和变量,如CatchException装饰器函数,report_execption函数、write_results_to_file函数等。在执行过程中还会调用其他模块中的函数,如toolbox模块的函数和predict模块的函数。
|
||||
|
||||
|
||||
@@ -82,13 +82,71 @@ def adjust_theme():
|
||||
return set_theme
|
||||
|
||||
advanced_css = """
|
||||
/* 设置表格的外边距为1em,内部单元格之间边框合并,空单元格显示. */
|
||||
.markdown-body table {
|
||||
border: 1px solid #ddd;
|
||||
margin: 1em 0;
|
||||
border-collapse: collapse;
|
||||
empty-cells: show;
|
||||
}
|
||||
|
||||
/* 设置表格单元格的内边距为5px,边框粗细为1.2px,颜色为--border-color-primary. */
|
||||
.markdown-body th, .markdown-body td {
|
||||
border: 1px solid #ddd;
|
||||
border: 1.2px solid var(--border-color-primary);
|
||||
padding: 5px;
|
||||
}
|
||||
|
||||
/* 设置表头背景颜色为rgba(175,184,193,0.2),透明度为0.2. */
|
||||
.markdown-body thead {
|
||||
background-color: rgba(175,184,193,0.2);
|
||||
}
|
||||
|
||||
/* 设置表头单元格的内边距为0.5em和0.2em. */
|
||||
.markdown-body thead th {
|
||||
padding: .5em .2em;
|
||||
}
|
||||
|
||||
/* 去掉列表前缀的默认间距,使其与文本线对齐. */
|
||||
.markdown-body ol, .markdown-body ul {
|
||||
padding-inline-start: 2em !important;
|
||||
}
|
||||
|
||||
/* 设定聊天气泡的样式,包括圆角、最大宽度和阴影等. */
|
||||
[class *= "message"] {
|
||||
border-radius: var(--radius-xl) !important;
|
||||
/* padding: var(--spacing-xl) !important; */
|
||||
/* font-size: var(--text-md) !important; */
|
||||
/* line-height: var(--line-md) !important; */
|
||||
/* min-height: calc(var(--text-md)*var(--line-md) + 2*var(--spacing-xl)); */
|
||||
/* min-width: calc(var(--text-md)*var(--line-md) + 2*var(--spacing-xl)); */
|
||||
}
|
||||
[data-testid = "bot"] {
|
||||
max-width: 95%;
|
||||
/* width: auto !important; */
|
||||
border-bottom-left-radius: 0 !important;
|
||||
}
|
||||
[data-testid = "user"] {
|
||||
max-width: 100%;
|
||||
/* width: auto !important; */
|
||||
border-bottom-right-radius: 0 !important;
|
||||
}
|
||||
|
||||
/* 行内代码的背景设为淡灰色,设定圆角和间距. */
|
||||
.markdown-body code {
|
||||
display: inline;
|
||||
white-space: break-spaces;
|
||||
border-radius: 6px;
|
||||
margin: 0 2px 0 2px;
|
||||
padding: .2em .4em .1em .4em;
|
||||
background-color: rgba(175,184,193,0.2);
|
||||
}
|
||||
/* 设定代码块的样式,包括背景颜色、内、外边距、圆角。 */
|
||||
.markdown-body pre code {
|
||||
display: block;
|
||||
overflow: auto;
|
||||
white-space: pre;
|
||||
background-color: rgba(175,184,193,0.2);
|
||||
border-radius: 10px;
|
||||
padding: 1em;
|
||||
margin: 1em 2em 1em 0.5em;
|
||||
}
|
||||
"""
|
||||
+36
-17
@@ -16,13 +16,13 @@ def get_reduce_token_percent(text):
|
||||
except:
|
||||
return 0.5, '不详'
|
||||
|
||||
def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], sys_prompt='', long_connection=True):
|
||||
def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[], sys_prompt='', long_connection=True):
|
||||
"""
|
||||
调用简单的predict_no_ui接口,但是依然保留了些许界面心跳功能,当对话太长时,会自动采用二分法截断
|
||||
i_say: 当前输入
|
||||
i_say_show_user: 显示到对话界面上的当前输入,例如,输入整个文件时,你绝对不想把文件的内容都糊到对话界面上
|
||||
chatbot: 对话界面句柄
|
||||
top_p, temperature: gpt参数
|
||||
top_p, api_key, temperature: gpt参数
|
||||
history: gpt参数 对话历史
|
||||
sys_prompt: gpt参数 sys_prompt
|
||||
long_connection: 是否采用更稳定的连接方式(推荐)
|
||||
@@ -39,9 +39,9 @@ def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temp
|
||||
while True:
|
||||
try:
|
||||
if long_connection:
|
||||
mutable[0] = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
mutable[0] = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
else:
|
||||
mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
break
|
||||
except ConnectionAbortedError as token_exceeded_error:
|
||||
# 尝试计算比例,尽可能多地保留文本
|
||||
@@ -108,15 +108,16 @@ def CatchException(f):
|
||||
装饰器函数,捕捉函数f中的异常并封装到一个生成器中返回,并显示到聊天当中。
|
||||
"""
|
||||
@wraps(f)
|
||||
def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def decorated(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
try:
|
||||
yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
|
||||
yield from f(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
|
||||
except Exception as e:
|
||||
from check_proxy import check_proxy
|
||||
from toolbox import get_conf
|
||||
proxies, = get_conf('proxies')
|
||||
tb_str = regular_txt_to_markdown(traceback.format_exc())
|
||||
chatbot[-1] = (chatbot[-1][0], f"[Local Message] 实验性函数调用出错: \n\n {tb_str} \n\n 当前代理可用性: \n\n {check_proxy(proxies)}")
|
||||
tb_str = '```\n' + traceback.format_exc() + '```'
|
||||
if len(chatbot) == 0: chatbot.append(["插件调度异常","异常原因"])
|
||||
chatbot[-1] = (chatbot[-1][0], f"[Local Message] 实验性函数调用出错: \n\n{tb_str} \n\n当前代理可用性: \n\n{check_proxy(proxies)}")
|
||||
yield chatbot, history, f'异常 {e}'
|
||||
return decorated
|
||||
|
||||
@@ -164,6 +165,23 @@ def markdown_convertion(txt):
|
||||
else:
|
||||
return pre + markdown.markdown(txt,extensions=['fenced_code','tables']) + suf
|
||||
|
||||
def close_up_code_segment_during_stream(gpt_reply):
|
||||
"""
|
||||
在gpt输出代码的中途(输出了前面的```,但还没输出完后面的```),补上后面的```
|
||||
"""
|
||||
if '```' not in gpt_reply: return gpt_reply
|
||||
if gpt_reply.endswith('```'): return gpt_reply
|
||||
|
||||
# 排除了以上两个情况,我们
|
||||
segments = gpt_reply.split('```')
|
||||
n_mark = len(segments) - 1
|
||||
if n_mark % 2 == 1:
|
||||
# print('输出代码片段中!')
|
||||
return gpt_reply+'\n```'
|
||||
else:
|
||||
return gpt_reply
|
||||
|
||||
|
||||
|
||||
def format_io(self, y):
|
||||
"""
|
||||
@@ -172,6 +190,7 @@ def format_io(self, y):
|
||||
if y is None or y == []: return []
|
||||
i_ask, gpt_reply = y[-1]
|
||||
i_ask = text_divide_paragraph(i_ask) # 输入部分太自由,预处理一波
|
||||
gpt_reply = close_up_code_segment_during_stream(gpt_reply) # 当代码输出半截的时候,试着补上后个```
|
||||
y[-1] = (
|
||||
None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code','tables']),
|
||||
None if gpt_reply is None else markdown_convertion(gpt_reply)
|
||||
@@ -284,7 +303,7 @@ def on_file_uploaded(files, chatbot, txt):
|
||||
def on_report_generated(files, chatbot):
|
||||
from toolbox import find_recent_files
|
||||
report_files = find_recent_files('gpt_log')
|
||||
if len(report_files) == 0: return report_files, chatbot
|
||||
if len(report_files) == 0: return files, chatbot
|
||||
# files.extend(report_files)
|
||||
chatbot.append(['汇总报告如何远程获取?', '汇总报告已经添加到右侧“文件上传区”(可能处于折叠状态),请查收。'])
|
||||
return report_files, chatbot
|
||||
@@ -294,14 +313,14 @@ def read_single_conf_with_lru_cache(arg):
|
||||
try: r = getattr(importlib.import_module('config_private'), arg)
|
||||
except: r = getattr(importlib.import_module('config'), arg)
|
||||
# 在读取API_KEY时,检查一下是不是忘了改config
|
||||
if arg=='API_KEY':
|
||||
# 正确的 API_KEY 是 "sk-" + 48 位大小写字母数字的组合
|
||||
API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", r)
|
||||
if API_MATCH:
|
||||
print(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
|
||||
else:
|
||||
assert False, "正确的 API_KEY 是 'sk-' + '48 位大小写字母数字' 的组合,请在config文件中修改API密钥, 添加海外代理之后再运行。" + \
|
||||
"(如果您刚更新过代码,请确保旧版config_private文件中没有遗留任何新增键值)"
|
||||
# if arg=='API_KEY':
|
||||
# # 正确的 API_KEY 是 "sk-" + 48 位大小写字母数字的组合
|
||||
# API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", r)
|
||||
# if API_MATCH:
|
||||
# print(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
|
||||
# else:
|
||||
# assert False, "正确的 API_KEY 是 'sk-' + '48 位大小写字母数字' 的组合,请在config文件中修改API密钥, 添加海外代理之后再运行。" + \
|
||||
# "(如果您刚更新过代码,请确保旧版config_private文件中没有遗留任何新增键值)"
|
||||
if arg=='proxies':
|
||||
if r is None:
|
||||
print('[PROXY] 网络代理状态:未配置。无代理状态下很可能无法访问。建议:检查USE_PROXY选项是否修改。')
|
||||
|
||||
Reference in New Issue
Block a user