538 lines
22 KiB
Python
538 lines
22 KiB
Python
import markdown
|
||
import mdtex2html
|
||
import threading
|
||
import importlib
|
||
import traceback
|
||
import importlib
|
||
import inspect
|
||
import re
|
||
from latex2mathml.converter import convert as tex2mathml
|
||
from functools import wraps, lru_cache
|
||
|
||
############################### 插件输入输出接驳区 #######################################
|
||
class ChatBotWithCookies(list):
|
||
def __init__(self, cookie):
|
||
self._cookies = cookie
|
||
|
||
def write_list(self, list):
|
||
for t in list:
|
||
self.append(t)
|
||
|
||
def get_list(self):
|
||
return [t for t in self]
|
||
|
||
def get_cookies(self):
|
||
return self._cookies
|
||
|
||
def ArgsGeneralWrapper(f):
|
||
"""
|
||
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。
|
||
"""
|
||
def decorated(cookies, txt, txt2, top_p, temperature, chatbot, history, system_prompt, *args):
|
||
txt_passon = txt
|
||
if txt == "" and txt2 != "": txt_passon = txt2
|
||
# 引入一个有cookie的chatbot
|
||
cookies.update({
|
||
'top_p':top_p,
|
||
'temperature':temperature,
|
||
})
|
||
llm_kwargs = {
|
||
'api_key': cookies['api_key'],
|
||
'llm_model': cookies['llm_model'],
|
||
'top_p':top_p,
|
||
'temperature':temperature,
|
||
}
|
||
plugin_kwargs = {
|
||
# 目前还没有
|
||
}
|
||
chatbot_with_cookie = ChatBotWithCookies(cookies)
|
||
chatbot_with_cookie.write_list(chatbot)
|
||
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||
return decorated
|
||
|
||
def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
|
||
"""
|
||
刷新用户界面
|
||
"""
|
||
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。"
|
||
yield chatbot.get_cookies(), chatbot.get_list(), history, msg
|
||
############################### ################## #######################################
|
||
##########################################################################################
|
||
|
||
def get_reduce_token_percent(text):
|
||
"""
|
||
* 此函数未来将被弃用
|
||
"""
|
||
try:
|
||
# text = "maximum context length is 4097 tokens. However, your messages resulted in 4870 tokens"
|
||
pattern = r"(\d+)\s+tokens\b"
|
||
match = re.findall(pattern, text)
|
||
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
|
||
max_limit = float(match[0]) - EXCEED_ALLO
|
||
current_tokens = float(match[1])
|
||
ratio = max_limit/current_tokens
|
||
assert ratio > 0 and ratio < 1
|
||
return ratio, str(int(current_tokens-max_limit))
|
||
except:
|
||
return 0.5, '不详'
|
||
|
||
|
||
def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], sys_prompt='', long_connection=True):
|
||
"""
|
||
* 此函数未来将被弃用（替代函数 request_gpt_model_in_new_thread_with_ui_alive 文件 chatgpt_academic/crazy_functions/crazy_utils）
|
||
|
||
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
|
||
i_say: 当前输入
|
||
i_say_show_user: 显示到对话界面上的当前输入，例如，输入整个文件时，你绝对不想把文件的内容都糊到对话界面上
|
||
chatbot: 对话界面句柄
|
||
top_p, temperature: gpt参数
|
||
history: gpt参数 对话历史
|
||
sys_prompt: gpt参数 sys_prompt
|
||
long_connection: 是否采用更稳定的连接方式（推荐）
|
||
"""
|
||
import time
|
||
from request_llm.bridge_chatgpt import predict_no_ui, predict_no_ui_long_connection
|
||
from toolbox import get_conf
|
||
TIMEOUT_SECONDS, MAX_RETRY = get_conf('TIMEOUT_SECONDS', 'MAX_RETRY')
|
||
# 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:
|
||
if long_connection:
|
||
mutable[0] = predict_no_ui_long_connection(
|
||
inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||
else:
|
||
mutable[0] = predict_no_ui(
|
||
inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||
break
|
||
except ConnectionAbortedError as token_exceeded_error:
|
||
# 尝试计算比例，尽可能多地保留文本
|
||
p_ratio, n_exceed = get_reduce_token_percent(
|
||
str(token_exceeded_error))
|
||
if len(history) > 0:
|
||
history = [his[int(len(his) * p_ratio):]
|
||
for his in history if his is not None]
|
||
else:
|
||
i_say = i_say[: int(len(i_say) * p_ratio)]
|
||
mutable[1] = f'警告，文本过长将进行截断，Token溢出数：{n_exceed}，截断比例：{(1-p_ratio):.0%}。'
|
||
except TimeoutError as e:
|
||
mutable[0] = '[Local Message] 请求超时。'
|
||
raise TimeoutError
|
||
except Exception as e:
|
||
mutable[0] = f'[Local Message] 异常：{str(e)}.'
|
||
raise RuntimeError(f'[Local Message] 异常：{str(e)}.')
|
||
# 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 from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||
time.sleep(1)
|
||
# 把gpt的输出从mutable中取出来
|
||
gpt_say = mutable[0]
|
||
if gpt_say == '[Local Message] Failed with timeout.':
|
||
raise TimeoutError
|
||
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
|
||
import time
|
||
if file_name is None:
|
||
# file_name = time.strftime("chatGPT分析报告%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
|
||
file_name = 'chatGPT分析报告' + \
|
||
time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.md'
|
||
os.makedirs('./gpt_log/', exist_ok=True)
|
||
with open(f'./gpt_log/{file_name}', 'w', encoding='utf8') as f:
|
||
f.write('# chatGPT 分析报告\n')
|
||
for i, content in enumerate(history):
|
||
try: # 这个bug没找到触发条件，暂时先这样顶一下
|
||
if type(content) != str:
|
||
content = str(content)
|
||
except:
|
||
continue
|
||
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(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||
try:
|
||
yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
|
||
except Exception as e:
|
||
from check_proxy import check_proxy
|
||
from toolbox import get_conf
|
||
proxies, = get_conf('proxies')
|
||
tb_str = '```\n' + traceback.format_exc() + '```'
|
||
if chatbot is None or len(chatbot) == 0:
|
||
chatbot = [["插件调度异常", "异常原因"]]
|
||
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 from update_ui(chatbot=chatbot, history=history, msg=f'异常 {e}') # 刷新界面
|
||
return decorated
|
||
|
||
|
||
def HotReload(f):
|
||
"""
|
||
HotReload的装饰器函数，用于实现Python函数插件的热更新。
|
||
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。
|
||
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。
|
||
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，
|
||
然后通过getattr函数获取函数名，并在新模块中重新加载函数。
|
||
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。
|
||
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。
|
||
"""
|
||
@wraps(f)
|
||
def decorated(*args, **kwargs):
|
||
fn_name = f.__name__
|
||
f_hot_reload = getattr(importlib.reload(inspect.getmodule(f)), fn_name)
|
||
yield from f_hot_reload(*args, **kwargs)
|
||
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):
|
||
lines[i] = lines[i].replace(" ", " ")
|
||
text = "</br>".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。
|
||
"""
|
||
pre = '<div class="markdown-body">'
|
||
suf = '</div>'
|
||
markdown_extension_configs = {
|
||
'mdx_math': {
|
||
'enable_dollar_delimiter': True,
|
||
'use_gitlab_delimiters': False,
|
||
},
|
||
}
|
||
find_equation_pattern = r'<script type="math/tex(?:.*?)>(.*?)</script>'
|
||
|
||
def tex2mathml_catch_exception(content, *args, **kwargs):
|
||
try:
|
||
content = tex2mathml(content, *args, **kwargs)
|
||
except:
|
||
content = content
|
||
return content
|
||
|
||
def replace_math_no_render(match):
|
||
content = match.group(1)
|
||
if 'mode=display' in match.group(0):
|
||
content = content.replace('\n', '</br>')
|
||
return f"<font color=\"#00FF00\">$$</font><font color=\"#FF00FF\">{content}</font><font color=\"#00FF00\">$$</font>"
|
||
else:
|
||
return f"<font color=\"#00FF00\">$</font><font color=\"#FF00FF\">{content}</font><font color=\"#00FF00\">$</font>"
|
||
|
||
def replace_math_render(match):
|
||
content = match.group(1)
|
||
if 'mode=display' in match.group(0):
|
||
if '\\begin{aligned}' in content:
|
||
content = content.replace('\\begin{aligned}', '\\begin{array}')
|
||
content = content.replace('\\end{aligned}', '\\end{array}')
|
||
content = content.replace('&', ' ')
|
||
content = tex2mathml_catch_exception(content, display="block")
|
||
return content
|
||
else:
|
||
return tex2mathml_catch_exception(content)
|
||
|
||
def markdown_bug_hunt(content):
|
||
"""
|
||
解决一个mdx_math的bug（单$包裹begin命令时多余<script>）
|
||
"""
|
||
content = content.replace('<script type="math/tex">\n<script type="math/tex; mode=display">', '<script type="math/tex; mode=display">')
|
||
content = content.replace('</script>\n</script>', '</script>')
|
||
return content
|
||
|
||
|
||
if ('$' in txt) and ('```' not in txt): # 有$标识的公式符号，且没有代码段```的标识
|
||
# convert everything to html format
|
||
split = markdown.markdown(text='---')
|
||
convert_stage_1 = markdown.markdown(text=txt, extensions=['mdx_math', 'fenced_code', 'tables', 'sane_lists'], extension_configs=markdown_extension_configs)
|
||
convert_stage_1 = markdown_bug_hunt(convert_stage_1)
|
||
# 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).
|
||
# 1. convert to easy-to-copy tex (do not render math)
|
||
convert_stage_2_1, n = re.subn(find_equation_pattern, replace_math_no_render, convert_stage_1, flags=re.DOTALL)
|
||
# 2. convert to rendered equation
|
||
convert_stage_2_2, n = re.subn(find_equation_pattern, replace_math_render, convert_stage_1, flags=re.DOTALL)
|
||
# cat them together
|
||
return pre + convert_stage_2_1 + f'{split}' + convert_stage_2_2 + suf
|
||
else:
|
||
return pre + markdown.markdown(txt, extensions=['fenced_code', 'codehilite', 'tables', 'sane_lists']) + suf
|
||
|
||
|
||
def close_up_code_segment_during_stream(gpt_reply):
|
||
"""
|
||
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```
|
||
|
||
Args:
|
||
gpt_reply (str): GPT模型返回的回复字符串。
|
||
|
||
Returns:
|
||
str: 返回一个新的字符串，将输出代码片段的“后面的```”补上。
|
||
|
||
"""
|
||
if '```' not in gpt_reply:
|
||
return gpt_reply
|
||
if gpt_reply.endswith('```'):
|
||
return gpt_reply
|
||
|
||
# 排除了以上两个情况，我们
|
||
segments = gpt_reply.split('```')
|
||
n_mark = len(segments) - 1
|
||
if n_mark % 2 == 1:
|
||
# print('输出代码片段中！')
|
||
return gpt_reply+'\n```'
|
||
else:
|
||
return gpt_reply
|
||
|
||
|
||
def format_io(self, y):
|
||
"""
|
||
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。
|
||
"""
|
||
if y is None or y == []:
|
||
return []
|
||
i_ask, gpt_reply = y[-1]
|
||
i_ask = text_divide_paragraph(i_ask) # 输入部分太自由，预处理一波
|
||
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```
|
||
y[-1] = (
|
||
None if i_ask is None else markdown.markdown(
|
||
i_ask, extensions=['fenced_code', 'tables']),
|
||
None if gpt_reply is None else markdown_convertion(gpt_reply)
|
||
)
|
||
return y
|
||
|
||
|
||
def find_free_port():
|
||
"""
|
||
返回当前系统中可用的未使用端口。
|
||
"""
|
||
import socket
|
||
from contextlib import closing
|
||
with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s:
|
||
s.bind(('', 0))
|
||
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
|
||
return s.getsockname()[1]
|
||
|
||
|
||
def extract_archive(file_path, dest_dir):
|
||
import zipfile
|
||
import tarfile
|
||
import os
|
||
# Get the file extension of the input file
|
||
file_extension = os.path.splitext(file_path)[1]
|
||
|
||
# Extract the archive based on its extension
|
||
if file_extension == '.zip':
|
||
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))
|
||
|
||
# 第三方库，需要预先pip install rarfile
|
||
# 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
|
||
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'
|
||
|
||
# 第三方库，需要预先pip install py7zr
|
||
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):
|
||
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}',
|
||
dest_dir=f'private_upload/{time_tag}/{file_origin_name}.extract')
|
||
moved_files = [fp for fp in glob.glob(
|
||
'private_upload/**/*', recursive=True)]
|
||
txt = f'private_upload/{time_tag}'
|
||
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
|
||
|
||
|
||
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
|
||
# files.extend(report_files)
|
||
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):
|
||
# 正确的 API_KEY 是 "sk-" + 48 位大小写字母数字的组合
|
||
API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", key)
|
||
return API_MATCH
|
||
|
||
@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)
|
||
# 在读取API_KEY时，检查一下是不是忘了改config
|
||
if arg == 'API_KEY':
|
||
if is_openai_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-' + '48 位大小写字母数字' 的组合，请在config文件中修改API密钥, 添加海外代理之后再运行。" + \
|
||
"（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）")
|
||
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。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):
|
||
# 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
|
||
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，
|
||
而在上下文执行结束时，__exit__()方法则会被调用。
|
||
"""
|
||
def __enter__(self):
|
||
return self
|
||
|
||
def __exit__(self, exc_type, exc_value, traceback):
|
||
return
|