import markdown, mdtex2html, threading from show_math import convert as convert_math from functools import wraps def predict_no_ui_but_counting_down(api, i_say, i_say_show_user, chatbot, top_p, temperature, history=[]): """ 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 """ import time try: from config_private import TIMEOUT_SECONDS, MAX_RETRY except: from config import TIMEOUT_SECONDS, MAX_RETRY from predict import predict_no_ui # 多线程的时候,需要一个mutable结构在不同线程之间传递信息 # list就是最简单的mutable结构,我们第一个位置放gpt输出,第二个位置传递报错信息 mutable = [None, ''] # multi-threading worker def mt(i_say, history): while True: try: mutable[0] = predict_no_ui(api, inputs=i_say, top_p=top_p, temperature=temperature, history=history) break except ConnectionAbortedError as e: if len(history) > 0: history = [his[len(his)//2:] for his in history if his is not None] mutable[1] = 'Warning! History conversation is too long, cut into half. ' else: i_say = i_say[:len(i_say)//2] mutable[1] = 'Warning! Input file is too long, cut into half. ' except TimeoutError as e: mutable[0] = '[Local Message] Failed with timeout' # 创建新线程发出http请求 thread_name = threading.Thread(target=mt, args=(i_say, history)); thread_name.start() # 原来的线程则负责持续更新UI,实现一个超时倒计时,并等待新线程的任务完成 cnt = 0 while thread_name.is_alive(): cnt += 1 chatbot[-1] = (i_say_show_user, f"[Local Message] {mutable[1]}waiting gpt response {cnt}/{TIMEOUT_SECONDS*2*(MAX_RETRY+1)}"+''.join(['.']*(cnt%4))) yield chatbot, history, '正常' time.sleep(1) # 把gpt的输出从mutable中取出来 gpt_say = mutable[0] return gpt_say def write_results_to_file(history, file_name=None): """ 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。 """ import os, time if file_name is None: file_name = time.strftime("chatGPT分析报告%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md' os.makedirs('./gpt_log/', exist_ok=True) with open(f'./gpt_log/{file_name}', 'w') as f: f.write('# chatGPT 分析报告\n') for i, content in enumerate(history): if i%2==0: f.write('## ') f.write(content) f.write('\n\n') res = '以上材料已经被写入' + os.path.abspath(f'./gpt_log/{file_name}') print(res) return res def regular_txt_to_markdown(text): """ 将普通文本转换为Markdown格式的文本。 """ text = text.replace('\n', '\n\n') text = text.replace('\n\n\n', '\n\n') text = text.replace('\n\n\n', '\n\n') return text 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(api, txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT): try: yield from f(api, txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT) except Exception as e: import traceback from check_proxy import check_proxy try: from config_private import proxies except: from config import 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 def report_execption(chatbot, history, a, b): """ 向chatbot中添加错误信息 """ chatbot.append((a, b)) history.append(a); history.append(b) def text_divide_paragraph(text): """ 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。 """ if '```' in text: # careful input return text else: # wtf input lines = text.split("\n") for i, line in enumerate(lines): if i!=0: lines[i] = "
"+lines[i].replace(" ", " ")+"
" text = "".join(lines) return text def markdown_convertion(txt): """ 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。 """ if ('$' in txt) and ('```' not in txt): return markdown.markdown(txt,extensions=['fenced_code','tables']) + '