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import markdown, mdtex2html, threading, importlib, traceback |
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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=[], sys_prompt=''): |
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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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from predict import predict_no_ui |
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from toolbox import get_conf |
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TIMEOUT_SECONDS, MAX_RETRY = get_conf('TIMEOUT_SECONDS', 'MAX_RETRY') |
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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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sys_prompt=sys_prompt) |
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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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raise TimeoutError |
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thread_name = threading.Thread(target=mt, args=(i_say, history)); |
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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, |
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f"[Local Message] {mutable[1]}waiting gpt response {cnt}/{TIMEOUT_SECONDS * 2 * (MAX_RETRY + 1)}" + ''.join( |
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['.'] * (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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if gpt_say == '[Local Message] Failed with timeout.': raise TimeoutError |
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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 = 'chatGPT分析报告' + 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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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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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 = regular_txt_to_markdown(traceback.format_exc()) |
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chatbot[-1] = ( |
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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); |
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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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lines[i] = lines[i].replace(" ", " ") |
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text = "</br>".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 or y == []: 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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elif file_extension == '.rar': |
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try: |
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import rarfile |
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with rarfile.RarFile(file_path) as rf: |
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rf.extractall(path=dest_dir) |
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print("Successfully extracted rar archive to {}".format(dest_dir)) |
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except: |
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print("rar格式需要安装额外依赖") |
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elif file_extension == '.7z': |
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try: |
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import py7zr |
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with py7zr.SevenZipFile(file_path, mode='r') as f: |
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f.extractall(path=dest_dir) |
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except: |
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print("7z格式需要安装额外依赖") |
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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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if os.path.isdir(file_path): continue |
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recent_files.append(file_path) |
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return recent_files |
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def on_file_uploaded(files, chatbot, txt): |
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if len(files) == 0: return chatbot, txt |
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import shutil, os, time, glob |
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from toolbox import extract_archive |
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try: |
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shutil.rmtree('./private_upload/') |
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except: |
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pass |
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time_tag = time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) |
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os.makedirs(f'private_upload/{time_tag}', exist_ok=True) |
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for file in files: |
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file_origin_name = os.path.basename(file.orig_name) |
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shutil.copy(file.name, f'private_upload/{time_tag}/{file_origin_name}') |
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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') |
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moved_files = [fp for fp in glob.glob('private_upload/**/*', recursive=True)] |
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txt = f'private_upload/{time_tag}' |
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moved_files_str = '\t\n\n'.join(moved_files) |
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chatbot.append(['我上传了文件,请查收', |
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f'[Local Message] 收到以下文件: \n\n{moved_files_str}\n\n调用路径参数已自动修正到: \n\n{txt}\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']) |
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return chatbot, txt |
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def on_report_generated(files, chatbot): |
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from toolbox import find_recent_files |
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report_files = find_recent_files('gpt_log') |
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if len(report_files) == 0: return report_files, chatbot |
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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,请查收。']) |
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return report_files, chatbot |
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def get_conf(*args): |
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res = [] |
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for arg in args: |
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try: |
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r = getattr(importlib.import_module('config_private'), arg) |
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except: |
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r = getattr(importlib.import_module('config'), arg) |
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res.append(r) |
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if arg == 'API_KEY' and len(r) != 51: |
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assert False, "正确的API_KEY密钥是51位,请在config文件中修改API密钥, 添加海外代理之后再运行。" + \ |
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"(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)" |
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return res |
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def clear_line_break(txt): |
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txt = txt.replace('\n', ' ') |
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txt = txt.replace(' ', ' ') |
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txt = txt.replace(' ', ' ') |
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return txt |
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