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import markdown |
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import importlib |
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import traceback |
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import inspect |
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import re |
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from latex2mathml.converter import convert as tex2mathml |
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from functools import wraps, lru_cache |
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|
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class ChatBotWithCookies(list): |
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def __init__(self, cookie): |
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self._cookies = cookie |
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|
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def write_list(self, list): |
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for t in list: |
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self.append(t) |
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|
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def get_list(self): |
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return [t for t in self] |
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|
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def get_cookies(self): |
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return self._cookies |
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|
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def ArgsGeneralWrapper(f): |
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""" |
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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。 |
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""" |
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def decorated(cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, *args): |
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from request_llm.bridge_all import model_info |
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txt_passon = txt |
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if txt == "" and txt2 != "": txt_passon = txt2 |
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|
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cookies.update({ |
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'top_p':top_p, |
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'temperature':temperature, |
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}) |
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llm_kwargs = { |
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'api_key': cookies['api_key'], |
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'llm_model': llm_model, |
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'top_p':top_p, |
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'max_length': max_length, |
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'temperature':temperature, |
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} |
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plugin_kwargs = { |
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|
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} |
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chatbot_with_cookie = ChatBotWithCookies(cookies) |
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chatbot_with_cookie.write_list(chatbot) |
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yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args) |
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return decorated |
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|
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def update_ui(chatbot, history, msg='正常', **kwargs): |
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""" |
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刷新用户界面 |
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""" |
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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。" |
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yield chatbot.get_cookies(), chatbot, history, msg |
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|
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def CatchException(f): |
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""" |
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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。 |
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""" |
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@wraps(f) |
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def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT): |
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try: |
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yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT) |
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except Exception as e: |
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from check_proxy import check_proxy |
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from toolbox import get_conf |
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proxies, = get_conf('proxies') |
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tb_str = '```\n' + traceback.format_exc() + '```' |
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if chatbot is None or len(chatbot) == 0: |
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chatbot = [["插件调度异常", "异常原因"]] |
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chatbot[-1] = (chatbot[-1][0], |
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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)}") |
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yield from update_ui(chatbot=chatbot, history=history, msg=f'异常 {e}') |
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return decorated |
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|
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def HotReload(f): |
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""" |
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HotReload的装饰器函数,用于实现Python函数插件的热更新。 |
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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。 |
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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。 |
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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, |
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然后通过getattr函数获取函数名,并在新模块中重新加载函数。 |
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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。 |
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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。 |
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""" |
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@wraps(f) |
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def decorated(*args, **kwargs): |
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fn_name = f.__name__ |
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f_hot_reload = getattr(importlib.reload(inspect.getmodule(f)), fn_name) |
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yield from f_hot_reload(*args, **kwargs) |
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return decorated |
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|
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def get_reduce_token_percent(text): |
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""" |
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* 此函数未来将被弃用 |
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""" |
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try: |
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|
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pattern = r"(\d+)\s+tokens\b" |
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match = re.findall(pattern, text) |
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EXCEED_ALLO = 500 |
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max_limit = float(match[0]) - EXCEED_ALLO |
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current_tokens = float(match[1]) |
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ratio = max_limit/current_tokens |
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assert ratio > 0 and ratio < 1 |
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return ratio, str(int(current_tokens-max_limit)) |
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except: |
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return 0.5, '不详' |
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|
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def write_results_to_file(history, file_name=None): |
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""" |
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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。 |
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""" |
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import os |
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import time |
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if file_name is None: |
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|
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file_name = 'chatGPT分析报告' + \ |
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time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md' |
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os.makedirs('./gpt_log/', exist_ok=True) |
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with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f: |
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f.write('# chatGPT 分析报告\n') |
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for i, content in enumerate(history): |
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try: |
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if type(content) != str: |
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content = str(content) |
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except: |
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continue |
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if i % 2 == 0: |
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f.write('## ') |
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f.write(content) |
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f.write('\n\n') |
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res = '以上材料已经被写入' + os.path.abspath(f'./gpt_log/{file_name}') |
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print(res) |
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return res |
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|
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|
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def regular_txt_to_markdown(text): |
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""" |
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将普通文本转换为Markdown格式的文本。 |
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""" |
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text = text.replace('\n', '\n\n') |
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text = text.replace('\n\n\n', '\n\n') |
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text = text.replace('\n\n\n', '\n\n') |
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return text |
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|
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def report_execption(chatbot, history, a, b): |
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""" |
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向chatbot中添加错误信息 |
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""" |
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chatbot.append((a, b)) |
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history.append(a) |
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history.append(b) |
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|
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|
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def text_divide_paragraph(text): |
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""" |
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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。 |
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""" |
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if '```' in text: |
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|
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return text |
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else: |
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|
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lines = text.split("\n") |
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for i, line in enumerate(lines): |
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lines[i] = lines[i].replace(" ", " ") |
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text = "</br>".join(lines) |
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return text |
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|
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def markdown_convertion(txt): |
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""" |
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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。 |
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""" |
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pre = '<div class="markdown-body">' |
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suf = '</div>' |
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markdown_extension_configs = { |
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'mdx_math': { |
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'enable_dollar_delimiter': True, |
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'use_gitlab_delimiters': False, |
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}, |
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} |
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find_equation_pattern = r'<script type="math/tex(?:.*?)>(.*?)</script>' |
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|
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def tex2mathml_catch_exception(content, *args, **kwargs): |
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try: |
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content = tex2mathml(content, *args, **kwargs) |
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except: |
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content = content |
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return content |
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|
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def replace_math_no_render(match): |
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content = match.group(1) |
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if 'mode=display' in match.group(0): |
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content = content.replace('\n', '</br>') |
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return f"<font color=\"#00FF00\">$$</font><font color=\"#FF00FF\">{content}</font><font color=\"#00FF00\">$$</font>" |
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else: |
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return f"<font color=\"#00FF00\">$</font><font color=\"#FF00FF\">{content}</font><font color=\"#00FF00\">$</font>" |
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|
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def replace_math_render(match): |
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content = match.group(1) |
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if 'mode=display' in match.group(0): |
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if '\\begin{aligned}' in content: |
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content = content.replace('\\begin{aligned}', '\\begin{array}') |
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content = content.replace('\\end{aligned}', '\\end{array}') |
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content = content.replace('&', ' ') |
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content = tex2mathml_catch_exception(content, display="block") |
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return content |
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else: |
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return tex2mathml_catch_exception(content) |
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|
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def markdown_bug_hunt(content): |
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""" |
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解决一个mdx_math的bug(单$包裹begin命令时多余<script>) |
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""" |
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content = content.replace('<script type="math/tex">\n<script type="math/tex; mode=display">', '<script type="math/tex; mode=display">') |
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content = content.replace('</script>\n</script>', '</script>') |
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return content |
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|
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if ('$' in txt) and ('```' not in txt): |
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|
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split = markdown.markdown(text='---') |
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convert_stage_1 = markdown.markdown(text=txt, extensions=['mdx_math', 'fenced_code', 'tables', 'sane_lists'], extension_configs=markdown_extension_configs) |
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convert_stage_1 = markdown_bug_hunt(convert_stage_1) |
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|
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convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL) |
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|
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convert_stage_2_2, n = re.subn(find_equation_pattern, replace_math_render, convert_stage_1, flags=re.DOTALL) |
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|
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return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf |
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else: |
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return pre + markdown.markdown(txt, extensions=['fenced_code', 'codehilite', 'tables', 'sane_lists']) + suf |
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|
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|
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def close_up_code_segment_during_stream(gpt_reply): |
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""" |
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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``` |
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|
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Args: |
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gpt_reply (str): GPT模型返回的回复字符串。 |
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|
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Returns: |
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str: 返回一个新的字符串,将输出代码片段的“后面的```”补上。 |
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|
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""" |
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if '```' not in gpt_reply: |
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return gpt_reply |
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if gpt_reply.endswith('```'): |
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return gpt_reply |
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|
|
|
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segments = gpt_reply.split('```') |
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n_mark = len(segments) - 1 |
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if n_mark % 2 == 1: |
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|
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return gpt_reply+'\n```' |
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else: |
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return gpt_reply |
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|
|
|
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def format_io(self, y): |
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""" |
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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。 |
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""" |
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if y is None or y == []: |
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return [] |
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i_ask, gpt_reply = y[-1] |
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i_ask = text_divide_paragraph(i_ask) |
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gpt_reply = close_up_code_segment_during_stream(gpt_reply) |
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y[-1] = ( |
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None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code', 'tables']), |
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None if gpt_reply is None else markdown_convertion(gpt_reply) |
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) |
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return y |
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|
|
|
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def find_free_port(): |
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""" |
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返回当前系统中可用的未使用端口。 |
|
""" |
|
import socket |
|
from contextlib import closing |
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with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s: |
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s.bind(('', 0)) |
|
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) |
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return s.getsockname()[1] |
|
|
|
|
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def extract_archive(file_path, dest_dir): |
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import zipfile |
|
import tarfile |
|
import os |
|
|
|
file_extension = os.path.splitext(file_path)[1] |
|
|
|
|
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if file_extension == '.zip': |
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with zipfile.ZipFile(file_path, 'r') as zipobj: |
|
zipobj.extractall(path=dest_dir) |
|
print("Successfully extracted zip archive to {}".format(dest_dir)) |
|
|
|
elif file_extension in ['.tar', '.gz', '.bz2']: |
|
with tarfile.open(file_path, 'r:*') as tarobj: |
|
tarobj.extractall(path=dest_dir) |
|
print("Successfully extracted tar archive to {}".format(dest_dir)) |
|
|
|
|
|
|
|
elif file_extension == '.rar': |
|
try: |
|
import rarfile |
|
with rarfile.RarFile(file_path) as rf: |
|
rf.extractall(path=dest_dir) |
|
print("Successfully extracted rar archive to {}".format(dest_dir)) |
|
except: |
|
print("Rar format requires additional dependencies to install") |
|
return '\n\n需要安装pip install rarfile来解压rar文件' |
|
|
|
|
|
elif file_extension == '.7z': |
|
try: |
|
import py7zr |
|
with py7zr.SevenZipFile(file_path, mode='r') as f: |
|
f.extractall(path=dest_dir) |
|
print("Successfully extracted 7z archive to {}".format(dest_dir)) |
|
except: |
|
print("7z format requires additional dependencies to install") |
|
return '\n\n需要安装pip install py7zr来解压7z文件' |
|
else: |
|
return '' |
|
return '' |
|
|
|
|
|
def find_recent_files(directory): |
|
""" |
|
me: find files that is created with in one minutes under a directory with python, write a function |
|
gpt: here it is! |
|
""" |
|
import os |
|
import time |
|
current_time = time.time() |
|
one_minute_ago = current_time - 60 |
|
recent_files = [] |
|
|
|
for filename in os.listdir(directory): |
|
file_path = os.path.join(directory, filename) |
|
if file_path.endswith('.log'): |
|
continue |
|
created_time = os.path.getmtime(file_path) |
|
if created_time >= one_minute_ago: |
|
if os.path.isdir(file_path): |
|
continue |
|
recent_files.append(file_path) |
|
|
|
return recent_files |
|
|
|
|
|
def on_file_uploaded(files, chatbot, txt, txt2, checkboxes): |
|
if len(files) == 0: |
|
return chatbot, txt |
|
import shutil |
|
import os |
|
import time |
|
import glob |
|
from toolbox import extract_archive |
|
try: |
|
shutil.rmtree('./private_upload/') |
|
except: |
|
pass |
|
time_tag = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) |
|
os.makedirs(f'private_upload/{time_tag}', exist_ok=True) |
|
err_msg = '' |
|
for file in files: |
|
file_origin_name = os.path.basename(file.orig_name) |
|
shutil.copy(file.name, f'private_upload/{time_tag}/{file_origin_name}') |
|
err_msg += extract_archive(f'private_upload/{time_tag}/{file_origin_name}', |
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dest_dir=f'private_upload/{time_tag}/{file_origin_name}.extract') |
|
moved_files = [fp for fp in glob.glob( |
|
'private_upload/**/*', recursive=True)] |
|
if "底部输入区" in checkboxes: |
|
txt = "" |
|
txt2 = f'private_upload/{time_tag}' |
|
else: |
|
txt = f'private_upload/{time_tag}' |
|
txt2 = "" |
|
moved_files_str = '\t\n\n'.join(moved_files) |
|
chatbot.append(['我上传了文件,请查收', |
|
f'[Local Message] 收到以下文件: \n\n{moved_files_str}' + |
|
f'\n\n调用路径参数已自动修正到: \n\n{txt}' + |
|
f'\n\n现在您点击任意实验功能时,以上文件将被作为输入参数'+err_msg]) |
|
return chatbot, txt, txt2 |
|
|
|
|
|
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 None, chatbot |
|
|
|
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 |
|
|
|
def is_openai_api_key(key): |
|
API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", key) |
|
return bool(API_MATCH) |
|
|
|
def is_api2d_key(key): |
|
if key.startswith('fk') and len(key) == 41: |
|
return True |
|
else: |
|
return False |
|
|
|
def is_any_api_key(key): |
|
if ',' in key: |
|
keys = key.split(',') |
|
for k in keys: |
|
if is_any_api_key(k): return True |
|
return False |
|
else: |
|
return is_openai_api_key(key) or is_api2d_key(key) |
|
|
|
|
|
def select_api_key(keys, llm_model): |
|
import random |
|
avail_key_list = [] |
|
key_list = keys.split(',') |
|
|
|
if llm_model.startswith('gpt-'): |
|
for k in key_list: |
|
if is_openai_api_key(k): avail_key_list.append(k) |
|
|
|
if llm_model.startswith('api2d-'): |
|
for k in key_list: |
|
if is_api2d_key(k): avail_key_list.append(k) |
|
|
|
if len(avail_key_list) == 0: |
|
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。") |
|
|
|
api_key = random.choice(avail_key_list) |
|
return api_key |
|
|
|
@lru_cache(maxsize=128) |
|
def read_single_conf_with_lru_cache(arg): |
|
from colorful import print亮红, print亮绿 |
|
try: |
|
r = getattr(importlib.import_module('config_private'), arg) |
|
except: |
|
r = getattr(importlib.import_module('config'), arg) |
|
|
|
if arg == 'API_KEY': |
|
if is_any_api_key(r): |
|
print亮绿(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功") |
|
else: |
|
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。") |
|
if arg == 'proxies': |
|
if r is None: |
|
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。') |
|
else: |
|
print亮绿('[PROXY] 网络代理状态:已配置。配置信息如下:', r) |
|
assert isinstance(r, dict), 'proxies格式错误,请注意proxies选项的格式,不要遗漏括号。' |
|
return r |
|
|
|
|
|
def get_conf(*args): |
|
|
|
res = [] |
|
for arg in args: |
|
r = read_single_conf_with_lru_cache(arg) |
|
res.append(r) |
|
return res |
|
|
|
|
|
def clear_line_break(txt): |
|
txt = txt.replace('\n', ' ') |
|
txt = txt.replace(' ', ' ') |
|
txt = txt.replace(' ', ' ') |
|
return txt |
|
|
|
|
|
class DummyWith(): |
|
""" |
|
这段代码定义了一个名为DummyWith的空上下文管理器, |
|
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。 |
|
上下文管理器是一种Python对象,用于与with语句一起使用, |
|
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。 |
|
上下文管理器必须实现两个方法,分别为 __enter__()和 __exit__()。 |
|
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, |
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而在上下文执行结束时,__exit__()方法则会被调用。 |
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""" |
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def __enter__(self): |
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return self |
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def __exit__(self, exc_type, exc_value, traceback): |
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return |
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