{"repo": "brenchcc/cloudpet", "files": {"toolbox.py": {"851962d055215bda70e04e7d6e894fe9da71317a": {"t": 1785768952.3324454, "n": 16788, "h": "296610eba8f6c9ec", "c": "import markdown\nimport importlib\nimport traceback\nimport inspect\nimport re\nfrom latex2mathml.converter import convert as tex2mathml\nfrom functools import wraps, lru_cache\n############################### 插件输入输出接驳区 #######################################\nclass ChatBotWithCookies(list):\n    def __init__(self, cookie):\n        self._cookies = cookie\n\n    def write_list(self, list):\n        for t in list:\n            self.append(t)\n\n    def get_list(self):\n        return [t for t in self]\n\n    def get_cookies(self):\n        return self._cookies\n\ndef ArgsGeneralWrapper(f):\n    \"\"\"\n    装饰器函数，用于重组输入参数，改变输入参数的顺序与结构。\n    \"\"\"\n    def decorated(cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, *args):\n        txt_passon = txt\n        if txt == \"\" and txt2 != \"\": txt_passon = txt2\n        # 引入一个有cookie的chatbot\n        cookies.update({\n            'top_p':top_p, \n            'temperature':temperature,\n        })\n        llm_kwargs = {\n            'api_key': cookies['api_key'],\n            'llm_model': llm_model,\n            'top_p':top_p, \n            'max_length': max_length,\n            'temperature':temperature,\n        }\n        plugin_kwargs = {\n            # 目前还没有\n        }\n        chatbot_with_cookie = ChatBotWithCookies(cookies)\n        chatbot_with_cookie.write_list(chatbot)\n        yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)\n    return decorated\n\ndef update_ui(chatbot, history, msg='正常', **kwargs):  # 刷新界面\n    \"\"\"\n    刷新用户界面\n    \"\"\"\n    assert isinstance(chatbot, ChatBotWithCookies), \"在传递chatbot的过程中不要将其丢弃。必要时，可用clear将其清空，然后用for+append循环重新赋值。\"\n    yield chatbot.get_cookies(), chatbot, history, msg\n\ndef CatchException(f):\n    \"\"\"\n    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。\n    \"\"\"\n    @wraps(f)\n    def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):\n        try:\n            yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)\n        except Exception as e:\n            from check_proxy import check_proxy\n            from toolbox import get_conf\n            proxies, = get_conf('proxies')\n            tb_str = '```\\n' + traceback.format_exc() + '```'\n            if chatbot is None or len(chatbot) == 0:\n                chatbot = [[\"插件调度异常\", \"异常原因\"]]\n            chatbot[-1] = (chatbot[-1][0],\n                           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)}\")\n            yield from update_ui(chatbot=chatbot, history=history, msg=f'异常 {e}') # 刷新界面\n    return decorated\n\n\ndef HotReload(f):\n    \"\"\"\n    HotReload的装饰器函数，用于实现Python函数插件的热更新。\n    函数热更新是指在不停止程序运行的情况下，更新函数代码，从而达到实时更新功能。\n    在装饰器内部，使用wraps(f)来保留函数的元信息，并定义了一个名为decorated的内部函数。\n    内部函数通过使用importlib模块的reload函数和inspect模块的getmodule函数来重新加载并获取函数模块，\n    然后通过getattr函数获取函数名，并在新模块中重新加载函数。\n    最后，使用yield from语句返回重新加载过的函数，并在被装饰的函数上执行。\n    最终，装饰器函数返回内部函数。这个内部函数可以将函数的原始定义更新为最新版本，并执行函数的新版本。\n    \"\"\"\n    @wraps(f)\n    def decorated(*args, **kwargs):\n        fn_name = f.__name__\n        f_hot_reload = getattr(importlib.reload(inspect.getmodule(f)), fn_name)\n        yield from f_hot_reload(*args, **kwargs)\n    return decorated\n\n\n####################################### 其他小工具 #####################################\n\ndef get_reduce_token_percent(text):\n    \"\"\"\n        * 此函数未来将被弃用\n    \"\"\"\n    try:\n        # text = \"maximum context length is 4097 tokens. However, your messages resulted in 4870 tokens\"\n        pattern = r\"(\\d+)\\s+tokens\\b\"\n        match = re.findall(pattern, text)\n        EXCEED_ALLO = 500  # 稍微留一点余地，否则在回复时会因余量太少出问题\n        max_limit = float(match[0]) - EXCEED_ALLO\n        current_tokens = float(match[1])\n        ratio = max_limit/current_tokens\n        assert ratio > 0 and ratio < 1\n        return ratio, str(int(current_tokens-max_limit))\n    except:\n        return 0.5, '不详'\n\n\n\ndef write_results_to_file(history, file_name=None):\n    \"\"\"\n    将对话记录history以Markdown格式写入文件中。如果没有指定文件名，则使用当前时间生成文件名。\n    \"\"\"\n    import os\n    import time\n    if file_name is None:\n        # file_name = time.strftime(\"chatGPT分析报告%Y-%m-%d-%H-%M-%S\", time.localtime()) + '.md'\n        file_name = 'chatGPT分析报告' + \\\n            time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.localtime()) + '.md'\n    os.makedirs('./gpt_log/', exist_ok=True)\n    with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:\n        f.write('# chatGPT 分析报告\\n')\n        for i, content in enumerate(history):\n            try:    # 这个bug没找到触发条件，暂时先这样顶一下\n                if type(content) != str:\n                    content = str(content)\n            except:\n                continue\n            if i % 2 == 0:\n                f.write('## ')\n            f.write(content)\n            f.write('\\n\\n')\n    res = '以上材料已经被写入' + os.path.abspath(f'./gpt_log/{file_name}')\n    print(res)\n    return res\n\n\ndef regular_txt_to_markdown(text):\n    \"\"\"\n    将普通文本转换为Markdown格式的文本。\n    \"\"\"\n    text = text.replace('\\n', '\\n\\n')\n    text = text.replace('\\n\\n\\n', '\\n\\n')\n    text = text.replace('\\n\\n\\n', '\\n\\n')\n    return text\n\n\n\n\ndef report_execption(chatbot, history, a, b):\n    \"\"\"\n    向chatbot中添加错误信息\n    \"\"\"\n    chatbot.append((a, b))\n    history.append(a)\n    history.append(b)\n\n\ndef text_divide_paragraph(text):\n    \"\"\"\n    将文本按照段落分隔符分割开，生成带有段落标签的HTML代码。\n    \"\"\"\n    if '```' in text:\n        # careful input\n        return text\n    else:\n        # wtf input\n        lines = text.split(\"\\n\")\n        for i, line in enumerate(lines):\n            lines[i] = lines[i].replace(\" \", \"&nbsp;\")\n        text = \"</br>\".join(lines)\n        return text\n\n\ndef markdown_convertion(txt):\n    \"\"\"\n    将Markdown格式的文本转换为HTML格式。如果包含数学公式，则先将公式转换为HTML格式。\n    \"\"\"\n    pre = '<div class=\"markdown-body\">'\n    suf = '</div>'\n    markdown_extension_configs = {\n        'mdx_math': {\n            'enable_dollar_delimiter': True,\n            'use_gitlab_delimiters': False,\n        },\n    }\n    find_equation_pattern = r'<script type=\"math/tex(?:.*?)>(.*?)</script>'\n\n    def tex2mathml_catch_exception(content, *args, **kwargs):\n        try:\n            content = tex2mathml(content, *args, **kwargs)\n        except:\n            content = content\n        return content\n\n    def replace_math_no_render(match):\n        content = match.group(1)\n        if 'mode=display' in match.group(0):\n            content = content.replace('\\n', '</br>')\n            return f\"<font color=\\\"#00FF00\\\">$$</font><font color=\\\"#FF00FF\\\">{content}</font><font color=\\\"#00FF00\\\">$$</font>\"\n        else:\n            return f\"<font color=\\\"#00FF00\\\">$</font><font color=\\\"#FF00FF\\\">{content}</font><font color=\\\"#00FF00\\\">$</font>\"\n\n    def replace_math_render(match):\n        content = match.group(1)\n        if 'mode=display' in match.group(0):\n            if '\\\\begin{aligned}' in content:\n                content = content.replace('\\\\begin{aligned}', '\\\\begin{array}')\n                content = content.replace('\\\\end{aligned}', '\\\\end{array}')\n                content = content.replace('&', ' ')\n            content = tex2mathml_catch_exception(content, display=\"block\")\n            return content\n        else:\n            return tex2mathml_catch_exception(content)\n        \n    def markdown_bug_hunt(content):\n        \"\"\"\n        解决一个mdx_math的bug（单$包裹begin命令时多余<script>）\n        \"\"\"\n        content = content.replace('<script type=\"math/tex\">\\n<script type=\"math/tex; mode=display\">', '<script type=\"math/tex; mode=display\">')\n        content = content.replace('</script>\\n</script>', '</script>')\n        return content\n    \n\n    if ('$' in txt) and ('```' not in txt):  # 有$标识的公式符号，且没有代码段```的标识\n        # convert everything to html format\n        split = markdown.markdown(text='---')\n        convert_stage_1 = markdown.markdown(text=txt, extensions=['mdx_math', 'fenced_code', 'tables', 'sane_lists'], extension_configs=markdown_extension_configs)\n        convert_stage_1 = markdown_bug_hunt(convert_stage_1)\n        # re.DOTALL: Make the '.' special character match any character at all, including a newline; without this flag, '.' will match anything except a newline. Corresponds to the inline flag (?s).\n        # 1. convert to easy-to-copy tex (do not render math)\n        convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL)\n        # 2. convert to rendered equation\n        convert_stage_2_2, n = re.subn(find_equation_pattern, replace_math_render, convert_stage_1, flags=re.DOTALL)\n        # cat them together\n        return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf\n    else:\n        return pre + markdown.markdown(txt, extensions=['fenced_code', 'codehilite', 'tables', 'sane_lists']) + suf\n\n\ndef close_up_code_segment_during_stream(gpt_reply):\n    \"\"\"\n    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```\n    \n    Args:\n        gpt_reply (str): GPT模型返回的回复字符串。\n\n    Returns:\n        str: 返回一个新的字符串，将输出代码片段的“后面的```”补上。\n\n    \"\"\"\n    if '```' not in gpt_reply:\n        return gpt_reply\n    if gpt_reply.endswith('```'):\n        return gpt_reply\n\n    # 排除了以上两个情况，我们\n    segments = gpt_reply.split('```')\n    n_mark = len(segments) - 1\n    if n_mark % 2 == 1:\n        # print('输出代码片段中！')\n        return gpt_reply+'\\n```'\n    else:\n        return gpt_reply\n\n\ndef format_io(self, y):\n    \"\"\"\n    将输入和输出解析为HTML格式。将y中最后一项的输入部分段落化，并将输出部分的Markdown和数学公式转换为HTML格式。\n    \"\"\"\n    if y is None or y == []:\n        return []\n    i_ask, gpt_reply = y[-1]\n    i_ask = text_divide_paragraph(i_ask)  # 输入部分太自由，预处理一波\n    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```\n    y[-1] = (\n        None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code', 'tables']),\n        None if gpt_reply is None else markdown_convertion(gpt_reply)\n    )\n    return y\n\n\ndef find_free_port():\n    \"\"\"\n    返回当前系统中可用的未使用端口。\n    \"\"\"\n    import socket\n    from contextlib import closing\n    with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s:\n        s.bind(('', 0))\n        s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)\n        return s.getsockname()[1]\n\n\ndef extract_archive(file_path, dest_dir):\n    import zipfile\n    import tarfile\n    import os\n    # Get the file extension of the input file\n    file_extension = os.path.splitext(file_path)[1]\n\n    # Extract the archive based on its extension\n    if file_extension == '.zip':\n        with zipfile.ZipFile(file_path, 'r') as zipobj:\n            zipobj.extractall(path=dest_dir)\n            print(\"Successfully extracted zip archive to {}\".format(dest_dir))\n\n    elif file_extension in ['.tar', '.gz', '.bz2']:\n        with tarfile.open(file_path, 'r:*') as tarobj:\n            tarobj.extractall(path=dest_dir)\n            print(\"Successfully extracted tar archive to {}\".format(dest_dir))\n\n    # 第三方库，需要预先pip install rarfile\n    # 此外，Windows上还需要安装winrar软件，配置其Path环境变量，如\"C:\\Program Files\\WinRAR\"才可以\n    elif file_extension == '.rar':\n        try:\n            import rarfile\n            with rarfile.RarFile(file_path) as rf:\n                rf.extractall(path=dest_dir)\n                print(\"Successfully extracted rar archive to {}\".format(dest_dir))\n        except:\n            print(\"Rar format requires additional dependencies to install\")\n            return '\\n\\n需要安装pip install rarfile来解压rar文件'\n\n    # 第三方库，需要预先pip install py7zr\n    elif file_extension == '.7z':\n        try:\n            import py7zr\n            with py7zr.SevenZipFile(file_path, mode='r') as f:\n                f.extractall(path=dest_dir)\n                print(\"Successfully extracted 7z archive to {}\".format(dest_dir))\n        except:\n            print(\"7z format requires additional dependencies to install\")\n            return '\\n\\n需要安装pip install py7zr来解压7z文件'\n    else:\n        return ''\n    return ''\n\n\ndef find_recent_files(directory):\n    \"\"\"\n        me: find files that is created with in one minutes under a directory with python, write a function\n        gpt: here it is!\n    \"\"\"\n    import os\n    import time\n    current_time = time.time()\n    one_minute_ago = current_time - 60\n    recent_files = []\n\n    for filename in os.listdir(directory):\n        file_path = os.path.join(directory, filename)\n        if file_path.endswith('.log'):\n            continue\n        created_time = os.path.getmtime(file_path)\n        if created_time >= one_minute_ago:\n            if os.path.isdir(file_path):\n                continue\n            recent_files.append(file_path)\n\n    return recent_files\n\n\ndef on_file_uploaded(files, chatbot, txt, txt2, checkboxes):\n    if len(files) == 0:\n        return chatbot, txt\n    import shutil\n    import os\n    import time\n    import glob\n    from toolbox import extract_archive\n    try:\n        shutil.rmtree('./private_upload/')\n    except:\n        pass\n    time_tag = time.strftime(\"%Y-%m-%d-%H-%M-%S\", time.localtime())\n    os.makedirs(f'private_upload/{time_tag}', exist_ok=True)\n    err_msg = ''\n    for file in files:\n        file_origin_name = os.path.basename(file.orig_name)\n        shutil.copy(file.name, f'private_upload/{time_tag}/{file_origin_name}')\n        err_msg += extract_archive(f'private_upload/{time_tag}/{file_origin_name}',\n                                   dest_dir=f'private_upload/{time_tag}/{file_origin_name}.extract')\n    moved_files = [fp for fp in glob.glob(\n        'private_upload/**/*', recursive=True)]\n    if \"底部输入区\" in checkboxes:\n        txt = \"\"\n        txt2 = f'private_upload/{time_tag}'\n    else:\n        txt = f'private_upload/{time_tag}'\n        txt2 = \"\"\n    moved_files_str = '\\t\\n\\n'.join(moved_files)\n    chatbot.append(['我上传了文件，请查收',\n                    f'[Local Message] 收到以下文件: \\n\\n{moved_files_str}' +\n                    f'\\n\\n调用路径参数已自动修正到: \\n\\n{txt}' +\n                    f'\\n\\n现在您点击任意“红颜色”标识的函数插件时，以上文件将被作为输入参数'+err_msg])\n    return chatbot, txt, txt2\n\n\ndef on_report_generated(files, chatbot):\n    from toolbox import find_recent_files\n    report_files = find_recent_files('gpt_log')\n    if len(report_files) == 0:\n        return None, chatbot\n    # files.extend(report_files)\n    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。'])\n    return report_files, chatbot\n\ndef is_openai_api_key(key):\n    API_MATCH = re.match(r\"sk-[a-zA-Z0-9]{48}$\", key)\n    return bool(API_MATCH)\n\ndef is_api2d_key(key):\n    if key.startswith('fk') and len(key) == 41:\n        return True\n    else:\n        return False\n\ndef is_any_api_key(key):\n    if ',' in key:\n        keys = key.split(',')\n        for k in keys:\n            if is_any_api_key(k): return True\n        return False\n    else:\n        return is_openai_api_key(key) or is_api2d_key(key)\n\n\ndef select_api_key(keys, llm_model):\n    import random\n    avail_key_list = []\n    key_list = keys.split(',')\n\n    if llm_model.startswith('gpt-'):\n        for k in key_list:\n            if is_openai_api_key(k): avail_key_list.append(k)\n\n    if llm_model.startswith('api2d-'):\n        for k in key_list:\n            if is_api2d_key(k): avail_key_list.append(k)\n\n    if len(avail_key_list) == 0:\n        raise RuntimeError(f\"您提供的api-key不满足要求，不包含任何可用于{llm_model}的api-key。\")\n\n    api_key = random.choice(avail_key_list) # 随机负载均衡\n    return api_key\n\n@lru_cache(maxsize=128)\ndef read_single_conf_with_lru_cache(arg):\n    from colorful import print亮红, print亮绿\n    try:\n        r = getattr(importlib.import_module('config_private'), arg)\n    except:\n        r = getattr(importlib.import_module('config'), arg)\n\n    # 在读取API_KEY时，检查一下是不是忘了改config\n    if arg == 'API_KEY':\n        if is_any_api_key(r):\n            print亮绿(f\"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功\")\n        else:\n            print亮红( \"[API_KEY] 正确的 API_KEY 是'sk'开头的51位密钥（OpenAI），或者 'fk'开头的41位密钥，请在config文件中修改API密钥之后再运行。\")\n\n    if arg == 'proxies':\n        if r is None:\n            print亮红('[PROXY] 网络代理状态：未配置。无代理状态下很可能无法访问OpenAI家族的模型。建议：检查USE_PROXY选项是否修改。')\n        else:\n            print亮绿('[PROXY] 网络代理状态：已配置。配置信息如下：', r)\n            assert isinstance(r, dict), 'proxies格式错误，请注意proxies选项的格式，不要遗漏括号。'\n    return r\n\n\ndef get_conf(*args):\n    # 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\n    res = []\n    for arg in args:\n        r = read_single_conf_with_lru_cache(arg)\n        res.append(r)\n    return res\n\n\ndef clear_line_break(txt):\n    txt = txt.replace('\\n', ' ')\n    txt = txt.replace('  ', ' ')\n    txt = txt.replace('  ', ' ')\n    return txt\n\n\nclass DummyWith():\n    \"\"\"\n    这段代码定义了一个名为DummyWith的空上下文管理器，\n    它的作用是……额……没用，即在代码结构不变得情况下取代其他的上下文管理器。\n    上下文管理器是一种Python对象，用于与with语句一起使用，\n    以确保一些资源在代码块执行期间得到正确的初始化和清理。\n    上下文管理器必须实现两个方法，分别为 __enter__()和 __exit__()。 \n    在上下文执行开始的情况下，__enter__()方法会在代码块被执行前被调用，\n    而在上下文执行结束时，__exit__()方法则会被调用。\n    \"\"\"\n    def __enter__(self):\n        return self\n\n    def __exit__(self, exc_type, exc_value, traceback):\n        return\n"}}}}