Spaces:
Build error
Build error
File size: 13,908 Bytes
363e455 93c13aa 0b03c79 93c13aa 61b4ea6 7186d9b 8b4b30a 7186d9b 2bf30d8 f04d975 8b4b30a f04d975 1805f08 8b4b30a 61b4ea6 8b4b30a 61b4ea6 f04d975 8b4b30a f04d975 7186d9b b017a3d 7186d9b f04d975 7186d9b 61b4ea6 7186d9b 32f36a6 fedc748 32f36a6 043a9ea 32f36a6 b9f2792 32f36a6 77408f7 32f36a6 93c13aa fedc748 93c13aa fedc748 93c13aa 2bf30d8 93c13aa 363e455 93c13aa fedc748 93c13aa fedc748 93c13aa 6dd83fb 93c13aa fedc748 93c13aa fedc748 1805f08 93c13aa fedc748 93c13aa 81741bc 1805f08 81741bc a360cd7 44e77dc a360cd7 44e77dc a098d08 e470ee1 44e77dc a360cd7 e470ee1 a360cd7 44e77dc a098d08 81741bc a098d08 1805f08 81741bc da19fa1 81741bc 17d9a06 81741bc 51bde97 a098d08 51bde97 a098d08 51bde97 a360cd7 a098d08 51bde97 2bf30d8 0b03c79 2bf30d8 44155bc ab879ca |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 |
import markdown, mdtex2html, threading, importlib, traceback, importlib, inspect
from show_math import convert as convert_math
from functools import wraps
import re
def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], sys_prompt=''):
"""
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
from predict import predict_no_ui
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:
mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
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.'
raise TimeoutError
# 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]
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, 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。
"""
@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 = 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 HotReload(f):
"""
装饰器函数,实现函数插件热更新
"""
@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。
"""
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 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
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.getctime(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, os, time, 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 report_files, 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,请查收。'])
return report_files, chatbot
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:
try: r = getattr(importlib.import_module('config_private'), arg)
except: r = getattr(importlib.import_module('config'), arg)
res.append(r)
# 在读取API_KEY时,检查一下是不是忘了改config
if arg=='API_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}$", r)
if API_MATCH:
print("您的 API_KEY 是: ", r, "\nAPI_KEY 导入成功")
else:
assert False, "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)"
return res
def clear_line_break(txt):
txt = txt.replace('\n', ' ')
txt = txt.replace(' ', ' ')
txt = txt.replace(' ', ' ')
return txt
import re
import unicodedata
def is_paragraph_break(match):
"""
根据给定的匹配结果来判断换行符是否表示段落分隔。
如果换行符前为句子结束标志(句号,感叹号,问号),且下一个字符为大写字母,则换行符更有可能表示段落分隔。
也可以根据之前的内容长度来判断段落是否已经足够长。
"""
prev_char, next_char = match.groups()
# 句子结束标志
sentence_endings = ".!?"
# 设定一个最小段落长度阈值
min_paragraph_length = 140
if prev_char in sentence_endings and next_char.isupper() and len(match.string[:match.start(1)]) > min_paragraph_length:
return "\n\n"
else:
return " "
def normalize_text(text):
"""
通过把连字(ligatures)等文本特殊符号转换为其基本形式来对文本进行归一化处理。
例如,将连字 "fi" 转换为 "f" 和 "i"。
"""
# 对文本进行归一化处理,分解连字
normalized_text = unicodedata.normalize("NFKD", text)
# 替换其他特殊字符
cleaned_text = re.sub(r'[^\x00-\x7F]+', '', normalized_text)
return cleaned_text
def clean_text(raw_text):
"""
对从 PDF 提取出的原始文本进行清洗和格式化处理。
1. 对原始文本进行归一化处理。
2. 替换跨行的连词,例如 “Espe-\ncially” 转换为 “Especially”。
3. 根据 heuristic 规则判断换行符是否是段落分隔,并相应地进行替换。
"""
# 对文本进行归一化处理
normalized_text = normalize_text(raw_text)
# 替换跨行的连词
text = re.sub(r'(\w+-\n\w+)', lambda m: m.group(1).replace('-\n', ''), normalized_text)
# 根据前后相邻字符的特点,找到原文本中的换行符
newlines = re.compile(r'(\S)\n(\S)')
# 根据 heuristic 规则,用空格或段落分隔符替换原换行符
final_text = re.sub(newlines, lambda m: m.group(1) + is_paragraph_break(m) + m.group(2), text)
return final_text.strip() |