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import importlib | |
import time | |
import inspect | |
import re | |
import os | |
import base64 | |
import gradio | |
import shutil | |
import glob | |
from functools import wraps | |
from shared_utils.config_loader import get_conf | |
from shared_utils.config_loader import set_conf | |
from shared_utils.config_loader import set_multi_conf | |
from shared_utils.config_loader import read_single_conf_with_lru_cache | |
from shared_utils.advanced_markdown_format import format_io | |
from shared_utils.advanced_markdown_format import markdown_convertion | |
from shared_utils.key_pattern_manager import select_api_key | |
from shared_utils.key_pattern_manager import is_any_api_key | |
from shared_utils.key_pattern_manager import what_keys | |
from shared_utils.connect_void_terminal import get_chat_handle | |
from shared_utils.connect_void_terminal import get_plugin_handle | |
from shared_utils.connect_void_terminal import get_plugin_default_kwargs | |
from shared_utils.connect_void_terminal import get_chat_default_kwargs | |
from shared_utils.text_mask import apply_gpt_academic_string_mask | |
from shared_utils.text_mask import build_gpt_academic_masked_string | |
from shared_utils.text_mask import apply_gpt_academic_string_mask_langbased | |
from shared_utils.text_mask import build_gpt_academic_masked_string_langbased | |
from shared_utils.handle_upload import html_local_file | |
from shared_utils.handle_upload import html_local_img | |
from shared_utils.handle_upload import file_manifest_filter_type | |
from shared_utils.handle_upload import extract_archive | |
pj = os.path.join | |
default_user_name = "default_user" | |
""" | |
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- | |
第一部分 | |
函数插件输入输出接驳区 | |
- ChatBotWithCookies: 带Cookies的Chatbot类,为实现更多强大的功能做基础 | |
- ArgsGeneralWrapper: 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 | |
- update_ui: 刷新界面用 yield from update_ui(chatbot, history) | |
- CatchException: 将插件中出的所有问题显示在界面上 | |
- HotReload: 实现插件的热更新 | |
- trimmed_format_exc: 打印traceback,为了安全而隐藏绝对地址 | |
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- | |
""" | |
class ChatBotWithCookies(list): | |
def __init__(self, cookie): | |
""" | |
cookies = { | |
'top_p': top_p, | |
'temperature': temperature, | |
'lock_plugin': bool, | |
"files_to_promote": ["file1", "file2"], | |
"most_recent_uploaded": { | |
"path": "uploaded_path", | |
"time": time.time(), | |
"time_str": "timestr", | |
} | |
} | |
""" | |
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ArgsGeneralWrapper,用于重组输入参数,改变输入参数的顺序与结构。 | |
该装饰器是大多数功能调用的入口。 | |
函数示意图:https://mermaid.live/edit#pako:eNqNVFtPGkEY_StkntoEDQtLoTw0sWqapjQxVWPabmOm7AiEZZcsQ9QiiW012qixqdeqqIn10geBh6ZR8PJnmAWe-hc6l3VhrWnLEzNzzvnO953ZyYOYoSIQAWOaMR5LQBN7hvoU3UN_g5iu7imAXEyT4wUF3Pd0dT3y9KGYYUJsmK8V0GPGs0-QjkyojZgwk0Fm82C2dVghX08U8EaoOHjOfoEMU0XmADRhOksVWnNLjdpM82qFzB6S5Q_WWsUhuqCc3JtAsVR_OoMnhyZwXgHWwbS1d4gnsLVZJp-P6mfVxveqAgqC70Jz_pQCOGDKM5xFdNNPDdilF6uSU_hOYqu4a3MHYDZLDzq5fodrC3PWcEaFGPUaRiqJWK_W9g9rvRITa4dhy_0nw67SiePMp3oSR6PPn41DGgllkvkizYwsrmtaejTFd8V4yekGmT1zqrt4XGlAy8WTuiPULF01LksZvukSajfQQRAxmYi5S0D81sDcyzapVdn6sYFHkjhhGyel3frVQnvsnbR23lEjlhIlaOJiFPWzU5G4tfNJo8ejwp47-TbvJkKKZvmxA6SKo16oaazJysfG6klr9T0pbTW2ZqzlL_XaT8fYbQLXe4mSmvoCZXMaa7FePW6s7jVqK9bujvse3WFjY5_Z4KfsA4oiPY4T7Drvn1tLJTbG1to1qR79ulgk89-oJbvZzbIwJty6u20LOReWa9BvwserUd9s9MIKc3x5TUWEoAhUyJK5y85w_yG-dFu_R9waoU7K581y8W_qLle35-rG9Nxcrz8QHRsc0K-r9NViYRT36KsFvCCNzDRMqvSVyzOKAnACpZECIvSvCs2UAhS9QHEwh43BST0GItjMIS_I8e-sLwnj9A262cxA_ZVh0OUY1LJiDSJ5MAEiUijYLUtBORR6KElyQPaCSRDpksNSd8AfluSgHPaFC17wjrOlbgbzyyFf4IFPDvoD_sJvnkdK-g | |
""" | |
def decorated(request: gradio.Request, cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg, *args): | |
txt_passon = txt | |
if txt == "" and txt2 != "": txt_passon = txt2 | |
# 引入一个有cookie的chatbot | |
if request.username is not None: | |
user_name = request.username | |
else: | |
user_name = default_user_name | |
cookies.update({ | |
'top_p': top_p, | |
'api_key': cookies['api_key'], | |
'llm_model': llm_model, | |
'temperature': temperature, | |
'user_name': user_name, | |
}) | |
llm_kwargs = { | |
'api_key': cookies['api_key'], | |
'llm_model': llm_model, | |
'top_p': top_p, | |
'max_length': max_length, | |
'temperature': temperature, | |
'client_ip': request.client.host, | |
'most_recent_uploaded': cookies.get('most_recent_uploaded') | |
} | |
plugin_kwargs = { | |
"advanced_arg": plugin_advanced_arg, | |
} | |
chatbot_with_cookie = ChatBotWithCookies(cookies) | |
chatbot_with_cookie.write_list(chatbot) | |
if cookies.get('lock_plugin', None) is None: | |
# 正常状态 | |
if len(args) == 0: # 插件通道 | |
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, request) | |
else: # 对话通道,或者基础功能通道 | |
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args) | |
else: | |
# 处理少数情况下的特殊插件的锁定状态 | |
module, fn_name = cookies['lock_plugin'].split('->') | |
f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name) | |
yield from f_hot_reload(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, request) | |
# 判断一下用户是否错误地通过对话通道进入,如果是,则进行提醒 | |
final_cookies = chatbot_with_cookie.get_cookies() | |
# len(args) != 0 代表“提交”键对话通道,或者基础功能通道 | |
if len(args) != 0 and 'files_to_promote' in final_cookies and len(final_cookies['files_to_promote']) > 0: | |
chatbot_with_cookie.append( | |
["检测到**滞留的缓存文档**,请及时处理。", "请及时点击“**保存当前对话**”获取所有滞留文档。"]) | |
yield from update_ui(chatbot_with_cookie, final_cookies['history'], msg="检测到被滞留的缓存文档") | |
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。" | |
cookies = chatbot.get_cookies() | |
# 备份一份History作为记录 | |
cookies.update({"history": history}) | |
# 解决插件锁定时的界面显示问题 | |
if cookies.get("lock_plugin", None): | |
label = ( | |
cookies.get("llm_model", "") | |
+ " | " | |
+ "正在锁定插件" | |
+ cookies.get("lock_plugin", None) | |
) | |
chatbot_gr = gradio.update(value=chatbot, label=label) | |
if cookies.get("label", "") != label: | |
cookies["label"] = label # 记住当前的label | |
elif cookies.get("label", None): | |
chatbot_gr = gradio.update(value=chatbot, label=cookies.get("llm_model", "")) | |
cookies["label"] = None # 清空label | |
else: | |
chatbot_gr = chatbot | |
yield cookies, chatbot_gr, history, msg | |
def update_ui_lastest_msg(lastmsg, chatbot, history, delay=1): # 刷新界面 | |
""" | |
刷新用户界面 | |
""" | |
if len(chatbot) == 0: | |
chatbot.append(["update_ui_last_msg", lastmsg]) | |
chatbot[-1] = list(chatbot[-1]) | |
chatbot[-1][-1] = lastmsg | |
yield from update_ui(chatbot=chatbot, history=history) | |
time.sleep(delay) | |
def trimmed_format_exc(): | |
import os, traceback | |
str = traceback.format_exc() | |
current_path = os.getcwd() | |
replace_path = "." | |
return str.replace(current_path, replace_path) | |
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(main_input, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, *args, **kwargs): | |
try: | |
yield from f(main_input, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, *args, **kwargs) | |
except Exception as e: | |
from check_proxy import check_proxy | |
from toolbox import get_conf | |
proxies = get_conf('proxies') | |
tb_str = '```\n' + trimmed_format_exc() + '```' | |
if len(chatbot_with_cookie) == 0: | |
chatbot_with_cookie.clear() | |
chatbot_with_cookie.append(["插件调度异常", "异常原因"]) | |
chatbot_with_cookie[-1] = (chatbot_with_cookie[-1][0], f"[Local Message] 插件调用出错: \n\n{tb_str} \n") | |
yield from update_ui(chatbot=chatbot_with_cookie, 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。 | |
""" | |
if get_conf("PLUGIN_HOT_RELOAD"): | |
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 | |
else: | |
return f | |
""" | |
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- | |
第二部分 | |
其他小工具: | |
- write_history_to_file: 将结果写入markdown文件中 | |
- regular_txt_to_markdown: 将普通文本转换为Markdown格式的文本。 | |
- report_exception: 向chatbot中添加简单的意外错误信息 | |
- text_divide_paragraph: 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。 | |
- markdown_convertion: 用多种方式组合,将markdown转化为好看的html | |
- format_io: 接管gradio默认的markdown处理方式 | |
- on_file_uploaded: 处理文件的上传(自动解压) | |
- on_report_generated: 将生成的报告自动投射到文件上传区 | |
- clip_history: 当历史上下文过长时,自动截断 | |
- get_conf: 获取设置 | |
- select_api_key: 根据当前的模型类别,抽取可用的api-key | |
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- | |
""" | |
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 write_history_to_file( | |
history, file_basename=None, file_fullname=None, auto_caption=True | |
): | |
""" | |
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_fullname is None: | |
if file_basename is not None: | |
file_fullname = pj(get_log_folder(), file_basename) | |
else: | |
file_fullname = pj(get_log_folder(), f"GPT-Academic-{gen_time_str()}.md") | |
os.makedirs(os.path.dirname(file_fullname), exist_ok=True) | |
with open(file_fullname, "w", encoding="utf8") as f: | |
f.write("# GPT-Academic Report\n") | |
for i, content in enumerate(history): | |
try: | |
if type(content) != str: | |
content = str(content) | |
except: | |
continue | |
if i % 2 == 0 and auto_caption: | |
f.write("## ") | |
try: | |
f.write(content) | |
except: | |
# remove everything that cannot be handled by utf8 | |
f.write(content.encode("utf-8", "ignore").decode()) | |
f.write("\n\n") | |
res = os.path.abspath(file_fullname) | |
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 report_exception(chatbot, history, a, b): | |
""" | |
向chatbot中添加错误信息 | |
""" | |
chatbot.append((a, b)) | |
history.extend([a, b]) | |
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 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 = [] | |
if not os.path.exists(directory): | |
os.makedirs(directory, exist_ok=True) | |
for filename in os.listdir(directory): | |
file_path = pj(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 file_already_in_downloadzone(file, user_path): | |
try: | |
parent_path = os.path.abspath(user_path) | |
child_path = os.path.abspath(file) | |
if os.path.samefile(os.path.commonpath([parent_path, child_path]), parent_path): | |
return True | |
else: | |
return False | |
except: | |
return False | |
def promote_file_to_downloadzone(file, rename_file=None, chatbot=None): | |
# 将文件复制一份到下载区 | |
import shutil | |
if chatbot is not None: | |
user_name = get_user(chatbot) | |
else: | |
user_name = default_user_name | |
if not os.path.exists(file): | |
raise FileNotFoundError(f"文件{file}不存在") | |
user_path = get_log_folder(user_name, plugin_name=None) | |
if file_already_in_downloadzone(file, user_path): | |
new_path = file | |
else: | |
user_path = get_log_folder(user_name, plugin_name="downloadzone") | |
if rename_file is None: | |
rename_file = f"{gen_time_str()}-{os.path.basename(file)}" | |
new_path = pj(user_path, rename_file) | |
# 如果已经存在,先删除 | |
if os.path.exists(new_path) and not os.path.samefile(new_path, file): | |
os.remove(new_path) | |
# 把文件复制过去 | |
if not os.path.exists(new_path): | |
shutil.copyfile(file, new_path) | |
# 将文件添加到chatbot cookie中 | |
if chatbot is not None: | |
if "files_to_promote" in chatbot._cookies: | |
current = chatbot._cookies["files_to_promote"] | |
else: | |
current = [] | |
if new_path not in current: # 避免把同一个文件添加多次 | |
chatbot._cookies.update({"files_to_promote": [new_path] + current}) | |
return new_path | |
def disable_auto_promotion(chatbot): | |
chatbot._cookies.update({"files_to_promote": []}) | |
return | |
def del_outdated_uploads(outdate_time_seconds, target_path_base=None): | |
if target_path_base is None: | |
user_upload_dir = get_conf("PATH_PRIVATE_UPLOAD") | |
else: | |
user_upload_dir = target_path_base | |
current_time = time.time() | |
one_hour_ago = current_time - outdate_time_seconds | |
# Get a list of all subdirectories in the user_upload_dir folder | |
# Remove subdirectories that are older than one hour | |
for subdirectory in glob.glob(f"{user_upload_dir}/*"): | |
subdirectory_time = os.path.getmtime(subdirectory) | |
if subdirectory_time < one_hour_ago: | |
try: | |
shutil.rmtree(subdirectory) | |
except: | |
pass | |
return | |
def to_markdown_tabs(head: list, tabs: list, alignment=":---:", column=False, omit_path=None): | |
""" | |
Args: | |
head: 表头:[] | |
tabs: 表值:[[列1], [列2], [列3], [列4]] | |
alignment: :--- 左对齐, :---: 居中对齐, ---: 右对齐 | |
column: True to keep data in columns, False to keep data in rows (default). | |
Returns: | |
A string representation of the markdown table. | |
""" | |
if column: | |
transposed_tabs = list(map(list, zip(*tabs))) | |
else: | |
transposed_tabs = tabs | |
# Find the maximum length among the columns | |
max_len = max(len(column) for column in transposed_tabs) | |
tab_format = "| %s " | |
tabs_list = "".join([tab_format % i for i in head]) + "|\n" | |
tabs_list += "".join([tab_format % alignment for i in head]) + "|\n" | |
for i in range(max_len): | |
row_data = [tab[i] if i < len(tab) else "" for tab in transposed_tabs] | |
row_data = file_manifest_filter_type(row_data, filter_=None) | |
# for dat in row_data: | |
# if (omit_path is not None) and os.path.exists(dat): | |
# dat = os.path.relpath(dat, omit_path) | |
tabs_list += "".join([tab_format % i for i in row_data]) + "|\n" | |
return tabs_list | |
def on_file_uploaded( | |
request: gradio.Request, files, chatbot, txt, txt2, checkboxes, cookies | |
): | |
""" | |
当文件被上传时的回调函数 | |
""" | |
if len(files) == 0: | |
return chatbot, txt | |
# 创建工作路径 | |
user_name = default_user_name if not request.username else request.username | |
time_tag = gen_time_str() | |
target_path_base = get_upload_folder(user_name, tag=time_tag) | |
os.makedirs(target_path_base, exist_ok=True) | |
# 移除过时的旧文件从而节省空间&保护隐私 | |
outdate_time_seconds = 3600 # 一小时 | |
del_outdated_uploads(outdate_time_seconds, get_upload_folder(user_name)) | |
# 逐个文件转移到目标路径 | |
upload_msg = "" | |
for file in files: | |
file_origin_name = os.path.basename(file.orig_name) | |
this_file_path = pj(target_path_base, file_origin_name) | |
shutil.move(file.name, this_file_path) | |
upload_msg += extract_archive( | |
file_path=this_file_path, dest_dir=this_file_path + ".extract" | |
) | |
# 整理文件集合 输出消息 | |
files = glob.glob(f"{target_path_base}/**/*", recursive=True) | |
moved_files = [fp for fp in files] | |
max_file_to_show = 10 | |
if len(moved_files) > max_file_to_show: | |
moved_files = moved_files[:max_file_to_show//2] + [f'... ( 📌省略{len(moved_files) - max_file_to_show}个文件的显示 ) ...'] + \ | |
moved_files[-max_file_to_show//2:] | |
moved_files_str = to_markdown_tabs(head=["文件"], tabs=[moved_files], omit_path=target_path_base) | |
chatbot.append( | |
[ | |
"我上传了文件,请查收", | |
f"[Local Message] 收到以下文件 (上传到路径:{target_path_base}): " + | |
f"\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现在您点击任意函数插件时,以上文件将被作为输入参数" + | |
upload_msg, | |
] | |
) | |
txt, txt2 = target_path_base, "" | |
if "浮动输入区" in checkboxes: | |
txt, txt2 = txt2, txt | |
# 记录近期文件 | |
cookies.update( | |
{ | |
"most_recent_uploaded": { | |
"path": target_path_base, | |
"time": time.time(), | |
"time_str": time_tag, | |
} | |
} | |
) | |
return chatbot, txt, txt2, cookies | |
def on_report_generated(cookies, files, chatbot): | |
# from toolbox import find_recent_files | |
# PATH_LOGGING = get_conf('PATH_LOGGING') | |
if "files_to_promote" in cookies: | |
report_files = cookies["files_to_promote"] | |
cookies.pop("files_to_promote") | |
else: | |
report_files = [] | |
# report_files = find_recent_files(PATH_LOGGING) | |
if len(report_files) == 0: | |
return cookies, None, chatbot | |
# files.extend(report_files) | |
file_links = "" | |
for f in report_files: | |
file_links += ( | |
f'<br/><a href="file={os.path.abspath(f)}" target="_blank">{f}</a>' | |
) | |
chatbot.append(["报告如何远程获取?", f"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。{file_links}"]) | |
return cookies, report_files, chatbot | |
def load_chat_cookies(): | |
API_KEY, LLM_MODEL, AZURE_API_KEY = get_conf( | |
"API_KEY", "LLM_MODEL", "AZURE_API_KEY" | |
) | |
AZURE_CFG_ARRAY, NUM_CUSTOM_BASIC_BTN = get_conf( | |
"AZURE_CFG_ARRAY", "NUM_CUSTOM_BASIC_BTN" | |
) | |
# deal with azure openai key | |
if is_any_api_key(AZURE_API_KEY): | |
if is_any_api_key(API_KEY): | |
API_KEY = API_KEY + "," + AZURE_API_KEY | |
else: | |
API_KEY = AZURE_API_KEY | |
if len(AZURE_CFG_ARRAY) > 0: | |
for azure_model_name, azure_cfg_dict in AZURE_CFG_ARRAY.items(): | |
if not azure_model_name.startswith("azure"): | |
raise ValueError("AZURE_CFG_ARRAY中配置的模型必须以azure开头") | |
AZURE_API_KEY_ = azure_cfg_dict["AZURE_API_KEY"] | |
if is_any_api_key(AZURE_API_KEY_): | |
if is_any_api_key(API_KEY): | |
API_KEY = API_KEY + "," + AZURE_API_KEY_ | |
else: | |
API_KEY = AZURE_API_KEY_ | |
customize_fn_overwrite_ = {} | |
for k in range(NUM_CUSTOM_BASIC_BTN): | |
customize_fn_overwrite_.update( | |
{ | |
"自定义按钮" | |
+ str(k + 1): { | |
"Title": r"", | |
"Prefix": r"请在自定义菜单中定义提示词前缀.", | |
"Suffix": r"请在自定义菜单中定义提示词后缀", | |
} | |
} | |
) | |
return { | |
"api_key": API_KEY, | |
"llm_model": LLM_MODEL, | |
"customize_fn_overwrite": customize_fn_overwrite_, | |
} | |
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……就是不起作用,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 | |
def run_gradio_in_subpath(demo, auth, port, custom_path): | |
""" | |
把gradio的运行地址更改到指定的二次路径上 | |
""" | |
def is_path_legal(path: str) -> bool: | |
""" | |
check path for sub url | |
path: path to check | |
return value: do sub url wrap | |
""" | |
if path == "/": | |
return True | |
if len(path) == 0: | |
print( | |
"ilegal custom path: {}\npath must not be empty\ndeploy on root url".format( | |
path | |
) | |
) | |
return False | |
if path[0] == "/": | |
if path[1] != "/": | |
print("deploy on sub-path {}".format(path)) | |
return True | |
return False | |
print( | |
"ilegal custom path: {}\npath should begin with '/'\ndeploy on root url".format( | |
path | |
) | |
) | |
return False | |
if not is_path_legal(custom_path): | |
raise RuntimeError("Ilegal custom path") | |
import uvicorn | |
import gradio as gr | |
from fastapi import FastAPI | |
app = FastAPI() | |
if custom_path != "/": | |
def read_main(): | |
return {"message": f"Gradio is running at: {custom_path}"} | |
app = gr.mount_gradio_app(app, demo, path=custom_path) | |
uvicorn.run(app, host="0.0.0.0", port=port) # , auth=auth | |
def clip_history(inputs, history, tokenizer, max_token_limit): | |
""" | |
reduce the length of history by clipping. | |
this function search for the longest entries to clip, little by little, | |
until the number of token of history is reduced under threshold. | |
通过裁剪来缩短历史记录的长度。 | |
此函数逐渐地搜索最长的条目进行剪辑, | |
直到历史记录的标记数量降低到阈值以下。 | |
""" | |
import numpy as np | |
from request_llms.bridge_all import model_info | |
def get_token_num(txt): | |
return len(tokenizer.encode(txt, disallowed_special=())) | |
input_token_num = get_token_num(inputs) | |
if max_token_limit < 5000: | |
output_token_expect = 256 # 4k & 2k models | |
elif max_token_limit < 9000: | |
output_token_expect = 512 # 8k models | |
else: | |
output_token_expect = 1024 # 16k & 32k models | |
if input_token_num < max_token_limit * 3 / 4: | |
# 当输入部分的token占比小于限制的3/4时,裁剪时 | |
# 1. 把input的余量留出来 | |
max_token_limit = max_token_limit - input_token_num | |
# 2. 把输出用的余量留出来 | |
max_token_limit = max_token_limit - output_token_expect | |
# 3. 如果余量太小了,直接清除历史 | |
if max_token_limit < output_token_expect: | |
history = [] | |
return history | |
else: | |
# 当输入部分的token占比 > 限制的3/4时,直接清除历史 | |
history = [] | |
return history | |
everything = [""] | |
everything.extend(history) | |
n_token = get_token_num("\n".join(everything)) | |
everything_token = [get_token_num(e) for e in everything] | |
# 截断时的颗粒度 | |
delta = max(everything_token) // 16 | |
while n_token > max_token_limit: | |
where = np.argmax(everything_token) | |
encoded = tokenizer.encode(everything[where], disallowed_special=()) | |
clipped_encoded = encoded[: len(encoded) - delta] | |
everything[where] = tokenizer.decode(clipped_encoded)[ | |
:-1 | |
] # -1 to remove the may-be illegal char | |
everything_token[where] = get_token_num(everything[where]) | |
n_token = get_token_num("\n".join(everything)) | |
history = everything[1:] | |
return history | |
""" | |
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- | |
第三部分 | |
其他小工具: | |
- zip_folder: 把某个路径下所有文件压缩,然后转移到指定的另一个路径中(gpt写的) | |
- gen_time_str: 生成时间戳 | |
- ProxyNetworkActivate: 临时地启动代理网络(如果有) | |
- objdump/objload: 快捷的调试函数 | |
=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- | |
""" | |
def zip_folder(source_folder, dest_folder, zip_name): | |
import zipfile | |
import os | |
# Make sure the source folder exists | |
if not os.path.exists(source_folder): | |
print(f"{source_folder} does not exist") | |
return | |
# Make sure the destination folder exists | |
if not os.path.exists(dest_folder): | |
print(f"{dest_folder} does not exist") | |
return | |
# Create the name for the zip file | |
zip_file = pj(dest_folder, zip_name) | |
# Create a ZipFile object | |
with zipfile.ZipFile(zip_file, "w", zipfile.ZIP_DEFLATED) as zipf: | |
# Walk through the source folder and add files to the zip file | |
for foldername, subfolders, filenames in os.walk(source_folder): | |
for filename in filenames: | |
filepath = pj(foldername, filename) | |
zipf.write(filepath, arcname=os.path.relpath(filepath, source_folder)) | |
# Move the zip file to the destination folder (if it wasn't already there) | |
if os.path.dirname(zip_file) != dest_folder: | |
os.rename(zip_file, pj(dest_folder, os.path.basename(zip_file))) | |
zip_file = pj(dest_folder, os.path.basename(zip_file)) | |
print(f"Zip file created at {zip_file}") | |
def zip_result(folder): | |
t = gen_time_str() | |
zip_folder(folder, get_log_folder(), f"{t}-result.zip") | |
return pj(get_log_folder(), f"{t}-result.zip") | |
def gen_time_str(): | |
import time | |
return time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) | |
def get_log_folder(user=default_user_name, plugin_name="shared"): | |
if user is None: | |
user = default_user_name | |
PATH_LOGGING = get_conf("PATH_LOGGING") | |
if plugin_name is None: | |
_dir = pj(PATH_LOGGING, user) | |
else: | |
_dir = pj(PATH_LOGGING, user, plugin_name) | |
if not os.path.exists(_dir): | |
os.makedirs(_dir) | |
return _dir | |
def get_upload_folder(user=default_user_name, tag=None): | |
PATH_PRIVATE_UPLOAD = get_conf("PATH_PRIVATE_UPLOAD") | |
if user is None: | |
user = default_user_name | |
if tag is None or len(tag) == 0: | |
target_path_base = pj(PATH_PRIVATE_UPLOAD, user) | |
else: | |
target_path_base = pj(PATH_PRIVATE_UPLOAD, user, tag) | |
return target_path_base | |
def is_the_upload_folder(string): | |
PATH_PRIVATE_UPLOAD = get_conf("PATH_PRIVATE_UPLOAD") | |
pattern = r"^PATH_PRIVATE_UPLOAD[\\/][A-Za-z0-9_-]+[\\/]\d{4}-\d{2}-\d{2}-\d{2}-\d{2}-\d{2}$" | |
pattern = pattern.replace("PATH_PRIVATE_UPLOAD", PATH_PRIVATE_UPLOAD) | |
if re.match(pattern, string): | |
return True | |
else: | |
return False | |
def get_user(chatbotwithcookies): | |
return chatbotwithcookies._cookies.get("user_name", default_user_name) | |
class ProxyNetworkActivate: | |
""" | |
这段代码定义了一个名为ProxyNetworkActivate的空上下文管理器, 用于给一小段代码上代理 | |
""" | |
def __init__(self, task=None) -> None: | |
self.task = task | |
if not task: | |
# 不给定task, 那么我们默认代理生效 | |
self.valid = True | |
else: | |
# 给定了task, 我们检查一下 | |
from toolbox import get_conf | |
WHEN_TO_USE_PROXY = get_conf("WHEN_TO_USE_PROXY") | |
self.valid = task in WHEN_TO_USE_PROXY | |
def __enter__(self): | |
if not self.valid: | |
return self | |
from toolbox import get_conf | |
proxies = get_conf("proxies") | |
if "no_proxy" in os.environ: | |
os.environ.pop("no_proxy") | |
if proxies is not None: | |
if "http" in proxies: | |
os.environ["HTTP_PROXY"] = proxies["http"] | |
if "https" in proxies: | |
os.environ["HTTPS_PROXY"] = proxies["https"] | |
return self | |
def __exit__(self, exc_type, exc_value, traceback): | |
os.environ["no_proxy"] = "*" | |
if "HTTP_PROXY" in os.environ: | |
os.environ.pop("HTTP_PROXY") | |
if "HTTPS_PROXY" in os.environ: | |
os.environ.pop("HTTPS_PROXY") | |
return | |
def objdump(obj, file="objdump.tmp"): | |
import pickle | |
with open(file, "wb+") as f: | |
pickle.dump(obj, f) | |
return | |
def objload(file="objdump.tmp"): | |
import pickle, os | |
if not os.path.exists(file): | |
return | |
with open(file, "rb") as f: | |
return pickle.load(f) | |
def Singleton(cls): | |
""" | |
一个单实例装饰器 | |
""" | |
_instance = {} | |
def _singleton(*args, **kargs): | |
if cls not in _instance: | |
_instance[cls] = cls(*args, **kargs) | |
return _instance[cls] | |
return _singleton | |
def get_pictures_list(path): | |
file_manifest = [f for f in glob.glob(f"{path}/**/*.jpg", recursive=True)] | |
file_manifest += [f for f in glob.glob(f"{path}/**/*.jpeg", recursive=True)] | |
file_manifest += [f for f in glob.glob(f"{path}/**/*.png", recursive=True)] | |
return file_manifest | |
def have_any_recent_upload_image_files(chatbot): | |
_5min = 5 * 60 | |
if chatbot is None: | |
return False, None # chatbot is None | |
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None) | |
if not most_recent_uploaded: | |
return False, None # most_recent_uploaded is None | |
if time.time() - most_recent_uploaded["time"] < _5min: | |
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None) | |
path = most_recent_uploaded["path"] | |
file_manifest = get_pictures_list(path) | |
if len(file_manifest) == 0: | |
return False, None | |
return True, file_manifest # most_recent_uploaded is new | |
else: | |
return False, None # most_recent_uploaded is too old | |
# Function to encode the image | |
def encode_image(image_path): | |
with open(image_path, "rb") as image_file: | |
return base64.b64encode(image_file.read()).decode("utf-8") | |
def get_max_token(llm_kwargs): | |
from request_llms.bridge_all import model_info | |
return model_info[llm_kwargs["llm_model"]]["max_token"] | |
def check_packages(packages=[]): | |
import importlib.util | |
for p in packages: | |
spam_spec = importlib.util.find_spec(p) | |
if spam_spec is None: | |
raise ModuleNotFoundError | |