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import markdown, mdtex2html, threading | |
from show_math import convert as convert_math | |
from functools import wraps | |
def predict_no_ui_but_counting_down(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(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' | |
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): | |
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。 | |
""" | |
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: | |
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] = "<p>"+lines[i].replace(" ", " ")+"</p>" | |
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']) + '<br><br>' + \ | |
markdown.markdown(convert_math(txt, splitParagraphs=False),extensions=['fenced_code','tables']) | |
else: | |
return markdown.markdown(txt,extensions=['fenced_code','tables']) | |
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: 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 | |
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)) | |
else: | |
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.getctime(file_path) | |
if created_time >= one_minute_ago: | |
recent_files.append(file_path) | |
return recent_files |