Revert "feat: 使用CSS完善表格、列表、代码块、对话气泡显示样式"

feat: 使用CSS完善表格、列表、代码块、对话气泡显示样式

README.md

@@ -2,9 +2,9 @@
 
 # ChatGPT 学术优化
 
-**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）**
+**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）**
 
-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）.
+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）.
 
 ```
 代码中参考了很多其他优秀项目中的设计，主要包括：
@@ -20,11 +20,11 @@ https://github.com/polarwinkel/mdtex2html
 
 > **Note**
 >
-> 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。
+> 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。
 >
-> 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。
+> 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。
 > 
-> 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。
+> 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。
 
 <div align="center">
     
@@ -35,16 +35,14 @@ https://github.com/polarwinkel/mdtex2html
 一键代码解释 | 可以正确显示代码、解释代码
 自定义快捷键 | 支持自定义快捷键
 配置代理服务器 | 支持配置代理服务器
-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)
-自我程序剖析 | [函数插件] 一键读懂本项目的源代码
-程序剖析 | [函数插件] 一键可以剖析其他Python/C/C++/Java项目树
-读论文 | [函数插件] 一键解读latex论文全文并生成摘要
-批量注释生成 | [函数插件] 一键批量生成函数注释
-chat分析报告生成 | [函数插件] 运行后自动生成总结汇报
-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
+模块化设计 | 支持自定义高阶的实验性功能
+自我程序剖析 | [实验性功能] 一键读懂本项目的源代码
+程序剖析 | [实验性功能] 一键可以剖析其他Python/C++项目
+读论文 | [实验性功能] 一键解读latex论文全文并生成摘要
+批量注释生成 | [实验性功能] 一键批量生成函数注释
+chat分析报告生成 | [实验性功能] 运行后自动生成总结汇报
 公式显示 | 可以同时显示公式的tex形式和渲染形式
 图片显示 | 可以在markdown中显示图片
-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
 支持GPT输出的markdown表格 | 可以输出支持GPT的markdown表格
 …… | ……
 
@@ -194,7 +192,7 @@ input区域 输入 ./crazy_functions/test_project/python/dqn ， 然后点击 "[
 如果你发明了更好用的学术快捷键，欢迎发issue或者pull requests！
 
 ## 配置代理
-### 方法一：常规方法
+
 在```config.py```中修改端口与代理软件对应
 
 <div align="center">
@@ -206,8 +204,6 @@ input区域 输入 ./crazy_functions/test_project/python/dqn ， 然后点击 "[
 ```
 python check_proxy.py
 ```
-### 方法二：纯新手教程
-[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)
 
 ## 兼容性测试
 
@@ -251,7 +247,7 @@ python check_proxy.py
 
 ### 模块化功能设计
 <div align="center">
-<img src="https://user-images.githubusercontent.com/96192199/229288270-093643c1-0018-487a-81e6-1d7809b6e90f.png" height="400" >
+<img src="https://user-images.githubusercontent.com/96192199/227504981-4c6c39c0-ae79-47e6-bffe-0e6442d9da65.png" height="400" >
 <img src="https://user-images.githubusercontent.com/96192199/227504931-19955f78-45cd-4d1c-adac-e71e50957915.png" height="400" >
 </div>
 
@@ -259,5 +255,5 @@ python check_proxy.py
 
 - (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
 - 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）
-
+- UI不够美观
 

app.py

@@ -1,150 +0,0 @@
-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
-from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf
-
-# 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, CHATBOT_HEIGHT = \
-    get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT')
-
-# 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
-if not AUTHENTICATION: AUTHENTICATION = None
-
-initial_prompt = "Serve me as a writing and programming assistant."
-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
-os.makedirs("gpt_log", exist_ok=True)
-try:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, encoding="utf-8")
-except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO)
-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！")
-
-# 一些普通功能模块
-from functional import get_functionals
-functional = get_functionals()
-
-# 高级函数插件
-from functional_crazy import get_crazy_functionals
-crazy_fns = get_crazy_functionals()
-
-# 处理markdown文本格式的转变
-gr.Chatbot.postprocess = format_io
-
-# 做一些外观色彩上的调整
-from theme import adjust_theme, advanced_css
-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()
-            chatbot.style(height=CHATBOT_HEIGHT)
-            history = gr.State([])
-        with gr.Column(scale=1):
-            with gr.Row():
-                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():
-                resetBtn = gr.Button("重置", variant="secondary"); resetBtn.style(size="sm")
-                stopBtn = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
-            with gr.Row():
-                from check_proxy import check_proxy
-                status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {check_proxy(proxies)}")
-            with gr.Accordion("基础功能区", open=True) as area_basic_fn:
-                with gr.Row():
-                    for k in functional:
-                        variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
-                        functional[k]["Button"] = gr.Button(k, variant=variant)
-            with gr.Accordion("函数插件区", open=True) as area_crazy_fn:
-                with gr.Row():
-                    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.")
-                with gr.Row():
-                    for k in crazy_fns:
-                        if not crazy_fns[k].get("AsButton", True): continue
-                        variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
-                        crazy_fns[k]["Button"] = gr.Button(k, variant=variant)
-                with gr.Row():
-                    with gr.Accordion("更多函数插件", open=True):
-                        dropdown_fn_list = [k for k in crazy_fns.keys() if not crazy_fns[k].get("AsButton", True)]
-                        with gr.Column(scale=1):
-                            dropdown = gr.Dropdown(dropdown_fn_list, value=r"打开插件列表", label="").style(container=False)
-                        with gr.Column(scale=1):
-                            switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary")
-                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 & 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 = {}
-        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))})
-        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, 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
-    # 提交按钮、重置按钮
-    cancel_handles.append(txt.submit(**predict_args)) #; txt.submit(**empty_txt_args) 在提交后清空输入栏
-    cancel_handles.append(submitBtn.click(**predict_args)) #; submitBtn.click(**empty_txt_args) 在提交后清空输入栏
-    resetBtn.click(lambda: ([], [], "已重置"), None, output_combo)
-    # 基础功能区的回调函数注册
-    for k in functional:
-        click_handle = functional[k]["Button"].click(predict, [*input_combo, gr.State(True), gr.State(k)], 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], [chatbot, txt])
-    # 函数插件-固定按钮区
-    for k in crazy_fns:
-        if not crazy_fns[k].get("AsButton", True): continue
-        click_handle = crazy_fns[k]["Button"].click(crazy_fns[k]["Function"], [*input_combo, gr.State(PORT)], output_combo)
-        click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
-        cancel_handles.append(click_handle)
-    # 函数插件-下拉菜单与随变按钮的互动
-    def on_dropdown_changed(k):
-        variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
-        return {switchy_bt: gr.update(value=k, variant=variant)}
-    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"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])
-    # def expand_file_area(file_upload, area_file_up):
-    #     if len(file_upload)>0: return {area_file_up: gr.update(open=True)}
-    # click_handle.then(expand_file_area, [file_upload, area_file_up], [area_file_up])
-    cancel_handles.append(click_handle)
-    # 终止按钮的回调函数注册
-    stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
-
-# 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():
-    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: http://localhost:{PORT}")
-    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)

config.py

@@ -22,13 +22,13 @@ 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 = 1115
+CHATBOT_HEIGHT = 1116
 
 # 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 = 7860
+WEB_PORT = -1
 
 # 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
@@ -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（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）
+# 设置用户名和密码
 AUTHENTICATION = [] # [("username", "password"), ("username2", "password2"), ...]

crazy_functions/下载arxiv论文翻译摘要.py

@@ -1,186 +0,0 @@
-from predict import predict_no_ui
-from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down, get_conf
-import re, requests, unicodedata, os
-
-def download_arxiv_(url_pdf):
-    if 'arxiv.org' not in url_pdf:
-        if ('.' in url_pdf) and ('/' not in url_pdf):
-            new_url = 'https://arxiv.org/abs/'+url_pdf
-            print('下载编号：', url_pdf, '自动定位：', new_url)
-            # download_arxiv_(new_url)
-            return download_arxiv_(new_url)
-        else:
-            print('不能识别的URL！')
-            return None
-    if 'abs' in url_pdf:
-        url_pdf = url_pdf.replace('abs', 'pdf')
-        url_pdf = url_pdf + '.pdf'
-
-    url_abs = url_pdf.replace('.pdf', '').replace('pdf', 'abs')
-    title, other_info = get_name(_url_=url_abs)
-
-    paper_id = title.split()[0]  # '[1712.00559]'
-    if '2' in other_info['year']:
-        title = other_info['year'] + ' ' + title
-
-    known_conf = ['NeurIPS', 'NIPS', 'Nature', 'Science', 'ICLR', 'AAAI']
-    for k in known_conf:
-        if k in other_info['comment']:
-            title = k + ' ' + title
-
-    download_dir = './gpt_log/arxiv/'
-    os.makedirs(download_dir, exist_ok=True)
-
-    title_str = title.replace('?', '？')\
-        .replace(':', '：')\
-        .replace('\"', '“')\
-        .replace('\n', '')\
-        .replace('  ', ' ')\
-        .replace('  ', ' ')
-
-    requests_pdf_url = url_pdf
-    file_path = download_dir+title_str
-    # if os.path.exists(file_path):
-    #     print('返回缓存文件')
-    #     return './gpt_log/arxiv/'+title_str
-
-    print('下载中')
-    proxies, = get_conf('proxies')
-    r = requests.get(requests_pdf_url, proxies=proxies)
-    with open(file_path, 'wb+') as f:
-        f.write(r.content)
-    print('下载完成')
-
-    # print('输出下载命令：','aria2c -o \"%s\" %s'%(title_str,url_pdf))
-    # subprocess.call('aria2c --all-proxy=\"172.18.116.150:11084\" -o \"%s\" %s'%(download_dir+title_str,url_pdf), shell=True)
-
-    x = "%s  %s %s.bib" % (paper_id, other_info['year'], other_info['authors'])
-    x = x.replace('?', '？')\
-        .replace(':', '：')\
-        .replace('\"', '“')\
-        .replace('\n', '')\
-        .replace('  ', ' ')\
-        .replace('  ', ' ')
-    return './gpt_log/arxiv/'+title_str, other_info
-
-
-def get_name(_url_):
-    import os
-    from bs4 import BeautifulSoup
-    print('正在获取文献名！')
-    print(_url_)
-
-    # arxiv_recall = {}
-    # if os.path.exists('./arxiv_recall.pkl'):
-    #     with open('./arxiv_recall.pkl', 'rb') as f:
-    #         arxiv_recall = pickle.load(f)
-
-    # if _url_ in arxiv_recall:
-    #     print('在缓存中')
-    #     return arxiv_recall[_url_]
-
-    proxies, = get_conf('proxies')
-    res = requests.get(_url_, proxies=proxies)
-
-    bs = BeautifulSoup(res.text, 'html.parser')
-    other_details = {}
-
-    # get year
-    try:
-        year = bs.find_all(class_='dateline')[0].text
-        year = re.search(r'(\d{4})', year, re.M | re.I).group(1)
-        other_details['year'] = year
-        abstract = bs.find_all(class_='abstract mathjax')[0].text
-        other_details['abstract'] = abstract
-    except:
-        other_details['year'] = ''
-        print('年份获取失败')
-
-    # get author
-    try:
-        authors = bs.find_all(class_='authors')[0].text
-        authors = authors.split('Authors:')[1]
-        other_details['authors'] = authors
-    except:
-        other_details['authors'] = ''
-        print('authors获取失败')
-
-    # get comment
-    try:
-        comment = bs.find_all(class_='metatable')[0].text
-        real_comment = None
-        for item in comment.replace('\n', ' ').split('   '):
-            if 'Comments' in item:
-                real_comment = item
-        if real_comment is not None:
-            other_details['comment'] = real_comment
-        else:
-            other_details['comment'] = ''
-    except:
-        other_details['comment'] = ''
-        print('年份获取失败')
-
-    title_str = BeautifulSoup(
-        res.text, 'html.parser').find('title').contents[0]
-    print('获取成功：', title_str)
-    # arxiv_recall[_url_] = (title_str+'.pdf', other_details)
-    # with open('./arxiv_recall.pkl', 'wb') as f:
-    #     pickle.dump(arxiv_recall, f)
-
-    return title_str+'.pdf', other_details
-
-
-
-@CatchException
-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，函数插件作者[binary-husky]。正在提取摘要并下载PDF文档……"
-    import glob
-    import os
-
-    # 基本信息：功能、贡献者
-    chatbot.append(["函数插件功能？", CRAZY_FUNCTION_INFO])
-    yield chatbot, history, '正常'
-
-    # 尝试导入依赖，如果缺少依赖，则给出安装建议
-    try:
-        import pdfminer, bs4
-    except:
-        report_execption(chatbot, history, 
-            a = f"解析项目: {txt}", 
-            b = f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pdfminer beautifulsoup4```。")
-        yield chatbot, history, '正常'
-        return
-
-    # 清空历史，以免输入溢出
-    history = []
-
-    # 提取摘要，下载PDF文档
-    try:
-        pdf_path, info = download_arxiv_(txt)
-    except:
-        report_execption(chatbot, history, 
-            a = f"解析项目: {txt}", 
-            b = f"下载pdf文件未成功")
-        yield chatbot, history, '正常'
-        return
-    
-    # 翻译摘要等
-    i_say =            f"请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。材料如下：{str(info)}"
-    i_say_show_user =  f'请你阅读以下学术论文相关的材料，提取摘要，翻译为中文。论文：{pdf_path}'
-    chatbot.append((i_say_show_user, "[Local Message] waiting gpt response."))
-    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, 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, 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 + "\n\nPDF文件也已经下载"))
-    yield chatbot, history, msg
-

crazy_functions/代码重写为全英文_多线程.py

@@ -5,7 +5,7 @@ from toolbox import CatchException, write_results_to_file
 
 
 @CatchException
-def 全项目切换英文(txt, top_p, api_key, temperature, chatbot, history, sys_prompt, WEB_PORT):
+def 全项目切换英文(txt, top_p, 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, api_key, temperature, chatbot, history, sy
             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, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
+        gpt_say = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, 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

crazy_functions/总结word文档.py

@@ -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, api_key, temperature, chatbot, history, systemPromptTxt):
+def 解析docx(file_manifest, project_folder, top_p, 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, api_key, temperature, chatb
         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, api_key, temperature,
+            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
             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, api_key, temperature, chatb
     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, api_key, temperature,
+        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
 
         chatbot[-1] = (i_say, gpt_say)
@@ -79,7 +79,7 @@ def 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatb
 
 
 @CatchException
-def 总结word文档(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 总结word文档(txt, top_p, 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, api_key, temperature, chatbot, history, systemP
         return
 
     # 开始正式执行任务
-    yield from 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
+    yield from 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)

crazy_functions/批量总结PDF文档.py

@@ -57,7 +57,7 @@ def clean_text(raw_text):
 
     return final_text.strip()
 
-def 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
+def 解析PDF(file_manifest, project_folder, top_p, 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, api_key, 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, api_key, 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, 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, api_key, 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, chatbot, top_p, api_key, 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, 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, api_key, temperature, chatbo
 
 
 @CatchException
-def 批量总结PDF文档(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 批量总结PDF文档(txt, top_p, 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, api_key, temperature, chatbot, history, sy
         return
 
     # 开始正式执行任务
-    yield from 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
+    yield from 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)

crazy_functions/批量总结PDF文档pdfminer.py

@@ -61,7 +61,7 @@ def readPdf(pdfPath):
     return outTextList
 
 
-def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
+def 解析Paper(file_manifest, project_folder, top_p, 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, api_key, temperature, chat
         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, api_key, 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, 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, api_key, temperature, chat
     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, api_key, 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, 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, api_key, temperature, chat
 
 
 @CatchException
-def 批量总结PDF文档pdfminer(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 批量总结PDF文档pdfminer(txt, top_p, 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, api_key, temperature, chatbot, his
         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, api_key, temperature, chatbot, history, systemPromptTxt)
+    yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
 

crazy_functions/生成函数注释.py

@@ -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, api_key, temperature, chatbot, history, systemPromptTxt):
+def 生成函数注释(file_manifest, project_folder, top_p, 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, api_key, temperatur
         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, api_key, 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, 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, api_key, temperatur
 
 
 @CatchException
-def 批量生成函数注释(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 批量生成函数注释(txt, top_p, 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, api_key, temperature, chatbot, history,
         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, api_key, temperature, chatbot, history, systemPromptTxt)
+    yield from 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)

crazy_functions/解析项目源代码.py

@@ -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, api_key, temperature, chatbot, history, systemPromptTxt):
+def 解析源代码(file_manifest, project_folder, top_p, 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, api_key, temperature,
             msg = '正常'
 
             # ** gpt request **
-            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
+            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
 
             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, api_key, temperature,
     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, api_key, 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, 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, api_key, temperature,
 
 
 @CatchException
-def 解析项目本身(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 解析项目本身(txt, top_p, 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, api_key, temperature, chatbot, history, syste
 
         if not fast_debug: 
             # ** gpt request **
-            # 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
+            # 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
 
             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, api_key, temperature, chatbot, history, syste
 
     if not fast_debug: 
         # ** gpt request **
-        # 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
+        # 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
 
         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, api_key, temperature, chatbot, history, syste
         yield chatbot, history, '正常'
 
 @CatchException
-def 解析一个Python项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 解析一个Python项目(txt, top_p, 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, api_key, temperature, chatbot, history,
         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, api_key, temperature, chatbot, history, systemPromptTxt)
+    yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
 
 
 @CatchException
-def 解析一个C项目的头文件(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 解析一个C项目的头文件(txt, top_p, 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, api_key, temperature, chatbot, h
         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, api_key, temperature, chatbot, history, systemPromptTxt)
+    yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
 
 @CatchException
-def 解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 解析一个C项目(txt, top_p, 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):
@@ -146,68 +146,5 @@ def 解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, syst
         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, api_key, temperature, chatbot, history, systemPromptTxt)
+    yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
 
-
-@CatchException
-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}")
-        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}")
-        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)

crazy_functions/读文章写摘要.py

@@ -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, api_key, temperature, chatbot, history, systemPromptTxt):
+def 解析Paper(file_manifest, project_folder, top_p, 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, api_key, temperature, chat
         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, api_key, 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, 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, api_key, temperature, chat
     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, api_key, 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, 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, api_key, temperature, chat
 
 
 @CatchException
-def 读文章写摘要(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 读文章写摘要(txt, top_p, 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, api_key, temperature, chatbot, history, syste
         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, api_key, temperature, chatbot, history, systemPromptTxt)
+    yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)

crazy_functions/高级功能函数模板.py

@@ -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, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+def 高阶功能模板函数(txt, top_p, 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, api_key, temperature, chatbot, history,
 
         # 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, api_key=api_key, temperature=temperature, history=[], 
+            inputs=i_say, top_p=top_p, 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)

functional_crazy.py

@@ -1,17 +1,19 @@
 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
     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
 
@@ -33,21 +35,6 @@ def get_crazy_functionals():
             "AsButton": False,  # 加入下拉菜单中
             "Function": 解析一个C项目
         },
-        "解析整个Go项目": {
-            "Color": "stop",    # 按钮颜色
-            "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
@@ -65,44 +52,33 @@ 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)
-        },
-    })
 
-    ###################### 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
+    # 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
         function_plugins.update({
-            "一键下载arxiv论文并翻译摘要（先在input输入编号，如1812.10695）": {
+            "[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(下载arxiv论文并翻译摘要)
-            }
+                "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)
+            },
         })
-    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
 
 

main.py

@@ -1,4 +1,3 @@
-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
@@ -13,8 +12,7 @@ PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
 if not AUTHENTICATION: AUTHENTICATION = None
 
 initial_prompt = "Serve me as a writing and programming assistant."
-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)"""
+title_html = """<h1 align="center">ChatGPT 学术优化</h1>"""
 
 # 问询记录, python 版本建议3.9+（越新越好）
 import logging
@@ -41,9 +39,6 @@ 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()
@@ -51,9 +46,7 @@ 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():
-                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)
+                txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
             with gr.Row():
                 submitBtn = gr.Button("提交", variant="primary")
             with gr.Row():
@@ -85,12 +78,12 @@ 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 & 交互界面布局 & Github地址", open=False):
+            with gr.Accordion("展开SysPrompt & GPT参数 & 交互界面布局", 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 = {}
@@ -99,7 +92,7 @@ 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, api_key, temperature, chatbot, history, system_prompt]
+    input_combo = [txt, top_p, 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
@@ -126,7 +119,7 @@ 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"请先从插件列表中选择"]: return 
+        if k in [r"打开插件列表", r"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])
@@ -148,4 +141,4 @@ def auto_opentab_delay():
 
 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)
+demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=True, server_port=PORT, auth=AUTHENTICATION)

predict.py

@@ -38,18 +38,18 @@ def get_full_error(chunk, stream_response):
             break
     return chunk
 
-def predict_no_ui(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
+def predict_no_ui(inputs, top_p, 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, api_key, temperature是chatGPT的内部调优参数
+        top_p, 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, api_key, temperature, history, system_prompt=sys_prompt, stream=False)
+    headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=False)
 
     retry = 0
     while True:
@@ -71,11 +71,11 @@ def predict_no_ui(inputs, top_p, api_key, 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, api_key, temperature, history=[], sys_prompt=""):
+def predict_no_ui_long_connection(inputs, top_p, 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, api_key, temperature, history, system_prompt=sys_prompt, stream=True)
+    headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=True)
 
     retry = 0
     while True:
@@ -112,13 +112,13 @@ def predict_no_ui_long_connection(inputs, top_p, api_key, temperature, history=[
     return result
 
 
-def predict(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_prompt='', 
+def predict(inputs, top_p, 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, api_key, temperature是chatGPT的内部调优参数
+        top_p, 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
@@ -136,7 +136,7 @@ def predict(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_
         chatbot.append((inputs, ""))
         yield chatbot, history, "等待响应"
 
-    headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt, stream)
+    headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
     history.append(inputs); history.append(" ")
 
     retry = 0
@@ -186,25 +186,23 @@ def predict(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_
                     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 = []    # 清除历史
+                        history = []
                     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 = '```\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
+                        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
                     return
 
-def generate_payload(inputs, top_p, api_key, temperature, history, system_prompt, stream):
+def generate_payload(inputs, top_p, 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

project_self_analysis.md

@@ -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, 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。
+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。
 
 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。
 

request_llm/README.md

@@ -1,36 +0,0 @@
-# 如何使用其他大语言模型（dev分支测试中）
-
-## 1. 先运行text-generation
-``` sh
-# 下载模型（ text-generation 这么牛的项目，别忘了给人家star ）
-git clone https://github.com/oobabooga/text-generation-webui.git
-
-# 安装text-generation的额外依赖
-pip install accelerate bitsandbytes flexgen gradio llamacpp markdown numpy peft requests rwkv safetensors sentencepiece tqdm datasets git+https://github.com/huggingface/transformers
-
-# 切换路径
-cd text-generation-webui
-
-# 下载模型
-python download-model.py facebook/galactica-1.3b
-# 其他可选如 facebook/opt-1.3b
-#           facebook/galactica-6.7b
-#           facebook/galactica-120b
-#           facebook/pygmalion-1.3b 等
-# 详情见 https://github.com/oobabooga/text-generation-webui
-
-# 启动text-generation，注意把模型的斜杠改成下划线
-python server.py --cpu --listen --listen-port 7860 --model facebook_galactica-1.3b
-```
-
-## 2. 修改config.py
-``` sh
-# LLM_MODEL格式较复杂   TGUI:[模型]@[ws地址]:[ws端口] ,   端口要和上面给定的端口一致
-LLM_MODEL = "TGUI:galactica-1.3b@localhost:7860"
-```
-
-## 3. 运行！
-``` sh
-cd chatgpt-academic
-python main.py
-```

request_llm/bridge_tgui.py

@@ -1,167 +0,0 @@
-'''
-Contributed by SagsMug. Modified by binary-husky
-https://github.com/oobabooga/text-generation-webui/pull/175
-'''
-
-import asyncio
-import json
-import random
-import string
-import websockets
-import logging
-import time
-import threading
-import importlib
-from toolbox import get_conf
-LLM_MODEL, = get_conf('LLM_MODEL')
-
-# "TGUI:galactica-1.3b@localhost:7860"
-model_name, addr_port = LLM_MODEL.split('@')
-assert ':' in addr_port, "LLM_MODEL 格式不正确！" + LLM_MODEL
-addr, port = addr_port.split(':')
-
-def random_hash():
-    letters = string.ascii_lowercase + string.digits
-    return ''.join(random.choice(letters) for i in range(9))
-
-async def run(context, max_token=512):
-    params = {
-        'max_new_tokens': max_token,
-        'do_sample': True,
-        'temperature': 0.5,
-        'top_p': 0.9,
-        'typical_p': 1,
-        'repetition_penalty': 1.05,
-        'encoder_repetition_penalty': 1.0,
-        'top_k': 0,
-        'min_length': 0,
-        'no_repeat_ngram_size': 0,
-        'num_beams': 1,
-        'penalty_alpha': 0,
-        'length_penalty': 1,
-        'early_stopping': True,
-        'seed': -1,
-    }
-    session = random_hash()
-
-    async with websockets.connect(f"ws://{addr}:{port}/queue/join") as websocket:
-        while content := json.loads(await websocket.recv()):
-            #Python3.10 syntax, replace with if elif on older
-            if content["msg"] ==  "send_hash":
-                await websocket.send(json.dumps({
-                    "session_hash": session,
-                    "fn_index": 12
-                }))
-            elif content["msg"] ==  "estimation":
-                pass
-            elif content["msg"] ==  "send_data":
-                await websocket.send(json.dumps({
-                    "session_hash": session,
-                    "fn_index": 12,
-                    "data": [
-                        context,
-                        params['max_new_tokens'],
-                        params['do_sample'],
-                        params['temperature'],
-                        params['top_p'],
-                        params['typical_p'],
-                        params['repetition_penalty'],
-                        params['encoder_repetition_penalty'],
-                        params['top_k'],
-                        params['min_length'],
-                        params['no_repeat_ngram_size'],
-                        params['num_beams'],
-                        params['penalty_alpha'],
-                        params['length_penalty'],
-                        params['early_stopping'],
-                        params['seed'],
-                    ]
-                }))
-            elif content["msg"] ==  "process_starts":
-                pass
-            elif content["msg"] in ["process_generating", "process_completed"]:
-                yield content["output"]["data"][0]
-                # You can search for your desired end indicator and 
-                #  stop generation by closing the websocket here
-                if (content["msg"] == "process_completed"):
-                    break
-
-
-
-
-
-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, 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
-    """
-    if additional_fn is not None:
-        import functional
-        importlib.reload(functional)    # 热更新prompt
-        functional = functional.get_functionals()
-        if "PreProcess" in functional[additional_fn]: inputs = functional[additional_fn]["PreProcess"](inputs)  # 获取预处理函数（如果有的话）
-        inputs = functional[additional_fn]["Prefix"] + inputs + functional[additional_fn]["Suffix"]
-
-    raw_input = "What I would like to say is the following: " + inputs
-    logging.info(f'[raw_input] {raw_input}')
-    history.extend([inputs, ""])
-    chatbot.append([inputs, ""])
-    yield chatbot, history, "等待响应"
-
-    prompt = inputs
-    tgui_say = ""
-
-    mutable = ["", time.time()]
-    def run_coorotine(mutable):
-        async def get_result(mutable):
-            async for response in run(prompt):
-                print(response[len(mutable[0]):])
-                mutable[0] = response
-                if (time.time() - mutable[1]) > 3: 
-                    print('exit when no listener')
-                    break
-        asyncio.run(get_result(mutable))
-
-    thread_listen = threading.Thread(target=run_coorotine, args=(mutable,), daemon=True)
-    thread_listen.start()
-
-    while thread_listen.is_alive():
-        time.sleep(1)
-        mutable[1] = time.time()
-        # Print intermediate steps
-        if tgui_say != mutable[0]:
-            tgui_say = mutable[0]
-            history[-1] = tgui_say
-            chatbot[-1] = (history[-2], history[-1])
-            yield chatbot, history, "status_text"
-
-    logging.info(f'[response] {tgui_say}')
-
-
-
-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 = ""
-    mutable = ["", time.time()]
-    def run_coorotine(mutable):
-        async def get_result(mutable):
-            async for response in run(prompt, max_token=20):
-                print(response[len(mutable[0]):])
-                mutable[0] = response
-                if (time.time() - mutable[1]) > 3: 
-                    print('exit when no listener')
-                    break
-        asyncio.run(get_result(mutable))
-    thread_listen = threading.Thread(target=run_coorotine, args=(mutable,))
-    thread_listen.start()
-    while thread_listen.is_alive():
-        time.sleep(1)
-        mutable[1] = time.time()
-    tgui_say = mutable[0]
-    return tgui_say

requirements.txt

@@ -3,7 +3,3 @@ requests[socks]
 mdtex2html
 Markdown
 latex2mathml
-pdfminer
-beautifulsoup4
-rarfile
-py7zr

theme.py

@@ -82,71 +82,13 @@ 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 {
-    margin: 1em 0;
+    border: 1px solid #ddd; 
     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: 1.2px solid var(--border-color-primary);
+    border: 1px solid #ddd; 
     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;
-}
 """

toolbox.py

@@ -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, api_key, temperature, history=[], sys_prompt='', long_connection=True):
+def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, 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, api_key, temperature: gpt参数
+        top_p, 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, api_
         while True:
             try:
                 if long_connection:
-                    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)
+                    mutable[0] = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
                 else:
-                    mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
+                    mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, 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
@@ -108,16 +108,15 @@ 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, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
+    def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
         try:
-            yield from f(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
+            yield from f(txt, top_p, 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 = '```\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)}")
+            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)}")
             yield chatbot, history, f'异常 {e}'
     return decorated
 
@@ -165,23 +164,6 @@ 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):
     """
@@ -190,7 +172,6 @@ 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)
@@ -303,7 +284,7 @@ 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 files, chatbot
+    if len(report_files) == 0: return report_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
@@ -313,14 +294,14 @@ 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。')