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import markdown, mdtex2html, threading |
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from show_math import convert as convert_math |
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from functools import wraps |
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def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]): |
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""" |
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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 |
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""" |
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import time |
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try: from config_private import TIMEOUT_SECONDS, MAX_RETRY |
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except: from config import TIMEOUT_SECONDS, MAX_RETRY |
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from predict import predict_no_ui |
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mutable = [None, ''] |
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def mt(i_say, history): |
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while True: |
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try: |
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mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history) |
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break |
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except ConnectionAbortedError as e: |
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if len(history) > 0: |
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history = [his[len(his)//2:] for his in history if his is not None] |
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mutable[1] = 'Warning! History conversation is too long, cut into half. ' |
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else: |
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i_say = i_say[:len(i_say)//2] |
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mutable[1] = 'Warning! Input file is too long, cut into half. ' |
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except TimeoutError as e: |
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mutable[0] = '[Local Message] Failed with timeout' |
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thread_name = threading.Thread(target=mt, args=(i_say, history)); thread_name.start() |
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cnt = 0 |
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while thread_name.is_alive(): |
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cnt += 1 |
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chatbot[-1] = (i_say_show_user, f"[Local Message] {mutable[1]}waiting gpt response {cnt}/{TIMEOUT_SECONDS*2*(MAX_RETRY+1)}"+''.join(['.']*(cnt%4))) |
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yield chatbot, history, '正常' |
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time.sleep(1) |
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gpt_say = mutable[0] |
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return gpt_say |
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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, time |
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if file_name is None: |
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file_name = time.strftime("chatGPT分析报告%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') 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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if i%2==0: 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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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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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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import traceback |
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from check_proxy import check_proxy |
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try: from config_private import proxies |
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except: from config import proxies |
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tb_str = regular_txt_to_markdown(traceback.format_exc()) |
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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)}") |
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yield chatbot, history, f'异常 {e}' |
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return decorated |
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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); history.append(b) |
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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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return text |
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else: |
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lines = text.split("\n") |
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for i, line in enumerate(lines): |
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if i!=0: lines[i] = "<p>"+lines[i].replace(" ", " ")+"</p>" |
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text = "".join(lines) |
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return text |
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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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if ('$' in txt) and ('```' not in txt): |
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return markdown.markdown(txt,extensions=['fenced_code','tables']) + '<br><br>' + \ |
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markdown.markdown(convert_math(txt, splitParagraphs=False),extensions=['fenced_code','tables']) |
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else: |
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return markdown.markdown(txt,extensions=['fenced_code','tables']) |
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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: 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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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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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。 |
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""" |
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import socket |
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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)) |
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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 |
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import tarfile |
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import os |
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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: |
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zipobj.extractall(path=dest_dir) |
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print("Successfully extracted zip archive to {}".format(dest_dir)) |
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elif file_extension in ['.tar', '.gz', '.bz2']: |
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with tarfile.open(file_path, 'r:*') as tarobj: |
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tarobj.extractall(path=dest_dir) |
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print("Successfully extracted tar archive to {}".format(dest_dir)) |
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else: |
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return |
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def find_recent_files(directory): |
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""" |
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me: find files that is created with in one minutes under a directory with python, write a function |
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gpt: here it is! |
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""" |
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import os |
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import time |
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current_time = time.time() |
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one_minute_ago = current_time - 60 |
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recent_files = [] |
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for filename in os.listdir(directory): |
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file_path = os.path.join(directory, filename) |
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if file_path.endswith('.log'): continue |
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created_time = os.path.getctime(file_path) |
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if created_time >= one_minute_ago: |
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recent_files.append(file_path) |
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return recent_files |