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config.py
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config.py
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# encoding:utf-8
import json
import logging
import os
import pickle
import copy
from common.log import logger
# 将所有可用的配置项写在字典里, 请使用小写字母
# 此处的配置值无实际意义,程序不会读取此处的配置,仅用于提示格式,请将配置加入到config.json中
available_setting = {
# openai api配置
"open_ai_api_key": "", # openai api key
# openai apibase,当use_azure_chatgpt为true时,需要设置对应的api base
"open_ai_api_base": "https://api.openai.com/v1",
"proxy": "", # openai使用的代理
# chatgpt模型, 当use_azure_chatgpt为true时,其名称为Azure上model deployment名称
"model": "gpt-3.5-turbo", # 可选择: gpt-4o, pt-4o-mini, gpt-4-turbo, claude-3-sonnet, wenxin, moonshot, qwen-turbo, xunfei, glm-4, minimax, gemini等模型,全部可选模型详见common/const.py文件
"bot_type": "", # 可选配置,使用兼容openai格式的三方服务时候,需填"chatGPT"。bot具体名称详见common/const.py文件列出的bot_type,如不填根据model名称判断,
"use_azure_chatgpt": False, # 是否使用azure的chatgpt
"azure_deployment_id": "", # azure 模型部署名称
"azure_api_version": "", # azure api版本
# Bot触发配置
"single_chat_prefix": ["bot", "@bot"], # 私聊时文本需要包含该前缀才能触发机器人回复
"single_chat_reply_prefix": "[bot] ", # 私聊时自动回复的前缀,用于区分真人
"single_chat_reply_suffix": "", # 私聊时自动回复的后缀,\n 可以换行
"group_chat_prefix": ["@bot"], # 群聊时包含该前缀则会触发机器人回复
"no_need_at": False, # 群聊回复时是否不需要艾特
"group_chat_reply_prefix": "", # 群聊时自动回复的前缀
"group_chat_reply_suffix": "", # 群聊时自动回复的后缀,\n 可以换行
"group_chat_keyword": [], # 群聊时包含该关键词则会触发机器人回复
"group_at_off": False, # 是否关闭群聊时@bot的触发
"group_name_white_list": ["ChatGPT测试群", "ChatGPT测试群2"], # 开启自动回复的群名称列表
"group_name_keyword_white_list": [], # 开启自动回复的群名称关键词列表
"group_chat_in_one_session": ["ChatGPT测试群"], # 支持会话上下文共享的群名称
"nick_name_black_list": [], # 用户昵称黑名单
"group_welcome_msg": "", # 配置新人进群固定欢迎语,不配置则使用随机风格欢迎
"trigger_by_self": False, # 是否允许机器人触发
"text_to_image": "dall-e-2", # 图片生成模型,可选 dall-e-2, dall-e-3
# Azure OpenAI dall-e-3 配置
"dalle3_image_style": "vivid", # 图片生成dalle3的风格,可选有 vivid, natural
"dalle3_image_quality": "hd", # 图片生成dalle3的质量,可选有 standard, hd
# Azure OpenAI DALL-E API 配置, 当use_azure_chatgpt为true时,用于将文字回复的资源和Dall-E的资源分开.
"azure_openai_dalle_api_base": "", # [可选] azure openai 用于回复图片的资源 endpoint,默认使用 open_ai_api_base
"azure_openai_dalle_api_key": "", # [可选] azure openai 用于回复图片的资源 key,默认使用 open_ai_api_key
"azure_openai_dalle_deployment_id":"", # [可选] azure openai 用于回复图片的资源 deployment id,默认使用 text_to_image
"image_proxy": True, # 是否需要图片代理,国内访问LinkAI时需要
"image_create_prefix": ["画", "看", "找"], # 开启图片回复的前缀
"concurrency_in_session": 1, # 同一会话最多有多少条消息在处理中,大于1可能乱序
"image_create_size": "256x256", # 图片大小,可选有 256x256, 512x512, 1024x1024 (dall-e-3默认为1024x1024)
"group_chat_exit_group": False,
# chatgpt会话参数
"expires_in_seconds": 3600, # 无操作会话的过期时间
# 人格描述
"character_desc": "你是ChatGPT, 一个由OpenAI训练的大型语言模型, 你旨在回答并解决人们的任何问题,并且可以使用多种语言与人交流。",
"conversation_max_tokens": 1000, # 支持上下文记忆的最多字符数
# chatgpt限流配置
"rate_limit_chatgpt": 20, # chatgpt的调用频率限制
"rate_limit_dalle": 50, # openai dalle的调用频率限制
# chatgpt api参数 参考https://platform.openai.com/docs/api-reference/chat/create
"temperature": 0.9,
"top_p": 1,
"frequency_penalty": 0,
"presence_penalty": 0,
"request_timeout": 180, # chatgpt请求超时时间,openai接口默认设置为600,对于难问题一般需要较长时间
"timeout": 120, # chatgpt重试超时时间,在这个时间内,将会自动重试
# Baidu 文心一言参数
"baidu_wenxin_model": "eb-instant", # 默认使用ERNIE-Bot-turbo模型
"baidu_wenxin_api_key": "", # Baidu api key
"baidu_wenxin_secret_key": "", # Baidu secret key
"baidu_wenxin_prompt_enabled": False, # Enable prompt if you are using ernie character model
# 讯飞星火API
"xunfei_app_id": "", # 讯飞应用ID
"xunfei_api_key": "", # 讯飞 API key
"xunfei_api_secret": "", # 讯飞 API secret
"xunfei_domain": "", # 讯飞模型对应的domain参数,Spark4.0 Ultra为 4.0Ultra,其他模型详见: https://www.xfyun.cn/doc/spark/Web.html
"xunfei_spark_url": "", # 讯飞模型对应的请求地址,Spark4.0 Ultra为 wss://spark-api.xf-yun.com/v4.0/chat,其他模型参考详见: https://www.xfyun.cn/doc/spark/Web.html
# claude 配置
"claude_api_cookie": "",
"claude_uuid": "",
# claude api key
"claude_api_key": "",
# 通义千问API, 获取方式查看文档 https://help.aliyun.com/document_detail/2587494.html
"qwen_access_key_id": "",
"qwen_access_key_secret": "",
"qwen_agent_key": "",
"qwen_app_id": "",
"qwen_node_id": "", # 流程编排模型用到的id,如果没有用到qwen_node_id,请务必保持为空字符串
# 阿里灵积(通义新版sdk)模型api key
"dashscope_api_key": "",
# Google Gemini Api Key
"gemini_api_key": "",
# wework的通用配置
"wework_smart": True, # 配置wework是否使用已登录的企业微信,False为多开
# 语音设置
"speech_recognition": True, # 是否开启语音识别
"group_speech_recognition": False, # 是否开启群组语音识别
"voice_reply_voice": False, # 是否使用语音回复语音,需要设置对应语音合成引擎的api key
"always_reply_voice": False, # 是否一直使用语音回复
"voice_to_text": "openai", # 语音识别引擎,支持openai,baidu,google,azure,xunfei,ali
"text_to_voice": "openai", # 语音合成引擎,支持openai,baidu,google,azure,xunfei,ali,pytts(offline),elevenlabs,edge(online)
"text_to_voice_model": "tts-1",
"tts_voice_id": "alloy",
# baidu 语音api配置, 使用百度语音识别和语音合成时需要
"baidu_app_id": "",
"baidu_api_key": "",
"baidu_secret_key": "",
# 1536普通话(支持简单的英文识别) 1737英语 1637粤语 1837四川话 1936普通话远场
"baidu_dev_pid": 1536,
# azure 语音api配置, 使用azure语音识别和语音合成时需要
"azure_voice_api_key": "",
"azure_voice_region": "japaneast",
# elevenlabs 语音api配置
"xi_api_key": "", # 获取ap的方法可以参考https://docs.elevenlabs.io/api-reference/quick-start/authentication
"xi_voice_id": "", # ElevenLabs提供了9种英式、美式等英语发音id,分别是“Adam/Antoni/Arnold/Bella/Domi/Elli/Josh/Rachel/Sam”
# 服务时间限制,目前支持itchat
"chat_time_module": False, # 是否开启服务时间限制
"chat_start_time": "00:00", # 服务开始时间
"chat_stop_time": "24:00", # 服务结束时间
# 翻译api
"translate": "baidu", # 翻译api,支持baidu
# baidu翻译api的配置
"baidu_translate_app_id": "", # 百度翻译api的appid
"baidu_translate_app_key": "", # 百度翻译api的秘钥
# itchat的配置
"hot_reload": False, # 是否开启热重载
# wechaty的配置
"wechaty_puppet_service_token": "", # wechaty的token
# wechatmp的配置
"wechatmp_token": "", # 微信公众平台的Token
"wechatmp_port": 8080, # 微信公众平台的端口,需要端口转发到80或443
"wechatmp_app_id": "", # 微信公众平台的appID
"wechatmp_app_secret": "", # 微信公众平台的appsecret
"wechatmp_aes_key": "", # 微信公众平台的EncodingAESKey,加密模式需要
# wechatcom的通用配置
"wechatcom_corp_id": "", # 企业微信公司的corpID
# wechatcomapp的配置
"wechatcomapp_token": "", # 企业微信app的token
"wechatcomapp_port": 9898, # 企业微信app的服务端口,不需要端口转发
"wechatcomapp_secret": "", # 企业微信app的secret
"wechatcomapp_agent_id": "", # 企业微信app的agent_id
"wechatcomapp_aes_key": "", # 企业微信app的aes_key
# 飞书配置
"feishu_port": 80, # 飞书bot监听端口
"feishu_app_id": "", # 飞书机器人应用APP Id
"feishu_app_secret": "", # 飞书机器人APP secret
"feishu_token": "", # 飞书 verification token
"feishu_bot_name": "", # 飞书机器人的名字
# 钉钉配置
"dingtalk_client_id": "", # 钉钉机器人Client ID
"dingtalk_client_secret": "", # 钉钉机器人Client Secret
"dingtalk_card_enabled": False,
# chatgpt指令自定义触发词
"clear_memory_commands": ["#清除记忆"], # 重置会话指令,必须以#开头
# channel配置
"channel_type": "", # 通道类型,支持:{wx,wxy,terminal,wechatmp,wechatmp_service,wechatcom_app,dingtalk}
"subscribe_msg": "", # 订阅消息, 支持: wechatmp, wechatmp_service, wechatcom_app
"debug": False, # 是否开启debug模式,开启后会打印更多日志
"appdata_dir": "", # 数据目录
# 插件配置
"plugin_trigger_prefix": "$", # 规范插件提供聊天相关指令的前缀,建议不要和管理员指令前缀"#"冲突
# 是否使用全局插件配置
"use_global_plugin_config": False,
"max_media_send_count": 3, # 单次最大发送媒体资源的个数
"media_send_interval": 1, # 发送图片的事件间隔,单位秒
# 智谱AI 平台配置
"zhipu_ai_api_key": "",
"zhipu_ai_api_base": "https://open.bigmodel.cn/api/paas/v4",
"moonshot_api_key": "",
"moonshot_base_url": "https://api.moonshot.cn/v1/chat/completions",
# LinkAI平台配置
"use_linkai": False,
"linkai_api_key": "",
"linkai_app_code": "",
"linkai_api_base": "https://api.link-ai.tech", # linkAI服务地址
"Minimax_api_key": "",
"Minimax_group_id": "",
"Minimax_base_url": "",
}
class Config(dict):
def __init__(self, d=None):
super().__init__()
if d is None:
d = {}
for k, v in d.items():
self[k] = v
# user_datas: 用户数据,key为用户名,value为用户数据,也是dict
self.user_datas = {}
def __getitem__(self, key):
if key not in available_setting:
raise Exception("key {} not in available_setting".format(key))
return super().__getitem__(key)
def __setitem__(self, key, value):
if key not in available_setting:
raise Exception("key {} not in available_setting".format(key))
return super().__setitem__(key, value)
def get(self, key, default=None):
try:
return self[key]
except KeyError as e:
return default
except Exception as e:
raise e
# Make sure to return a dictionary to ensure atomic
def get_user_data(self, user) -> dict:
if self.user_datas.get(user) is None:
self.user_datas[user] = {}
return self.user_datas[user]
def load_user_datas(self):
try:
with open(os.path.join(get_appdata_dir(), "user_datas.pkl"), "rb") as f:
self.user_datas = pickle.load(f)
logger.info("[Config] User datas loaded.")
except FileNotFoundError as e:
logger.info("[Config] User datas file not found, ignore.")
except Exception as e:
logger.info("[Config] User datas error: {}".format(e))
self.user_datas = {}
def save_user_datas(self):
try:
with open(os.path.join(get_appdata_dir(), "user_datas.pkl"), "wb") as f:
pickle.dump(self.user_datas, f)
logger.info("[Config] User datas saved.")
except Exception as e:
logger.info("[Config] User datas error: {}".format(e))
config = Config()
def drag_sensitive(config):
try:
if isinstance(config, str):
conf_dict: dict = json.loads(config)
conf_dict_copy = copy.deepcopy(conf_dict)
for key in conf_dict_copy:
if "key" in key or "secret" in key:
if isinstance(conf_dict_copy[key], str):
conf_dict_copy[key] = conf_dict_copy[key][0:3] + "*" * 5 + conf_dict_copy[key][-3:]
return json.dumps(conf_dict_copy, indent=4)
elif isinstance(config, dict):
config_copy = copy.deepcopy(config)
for key in config:
if "key" in key or "secret" in key:
if isinstance(config_copy[key], str):
config_copy[key] = config_copy[key][0:3] + "*" * 5 + config_copy[key][-3:]
return config_copy
except Exception as e:
logger.exception(e)
return config
return config
def load_config():
global config
config_path = "./config.json"
if not os.path.exists(config_path):
logger.info("配置文件不存在,将使用config-template.json模板")
config_path = "./config-template.json"
config_str = read_file(config_path)
logger.debug("[INIT] config str: {}".format(drag_sensitive(config_str)))
# 将json字符串反序列化为dict类型
config = Config(json.loads(config_str))
# override config with environment variables.
# Some online deployment platforms (e.g. Railway) deploy project from github directly. So you shouldn't put your secrets like api key in a config file, instead use environment variables to override the default config.
for name, value in os.environ.items():
name = name.lower()
if name in available_setting:
logger.info("[INIT] override config by environ args: {}={}".format(name, value))
try:
config[name] = eval(value)
except:
if value == "false":
config[name] = False
elif value == "true":
config[name] = True
else:
config[name] = value
if config.get("debug", False):
logger.setLevel(logging.DEBUG)
logger.debug("[INIT] set log level to DEBUG")
logger.info("[INIT] load config: {}".format(drag_sensitive(config)))
config.load_user_datas()
def get_root():
return os.path.dirname(os.path.abspath(__file__))
def read_file(path):
with open(path, mode="r", encoding="utf-8") as f:
return f.read()
def conf():
return config
def get_appdata_dir():
data_path = os.path.join(get_root(), conf().get("appdata_dir", ""))
if not os.path.exists(data_path):
logger.info("[INIT] data path not exists, create it: {}".format(data_path))
os.makedirs(data_path)
return data_path
def subscribe_msg():
trigger_prefix = conf().get("single_chat_prefix", [""])[0]
msg = conf().get("subscribe_msg", "")
return msg.format(trigger_prefix=trigger_prefix)
# global plugin config
plugin_config = {}
def write_plugin_config(pconf: dict):
"""
写入插件全局配置
:param pconf: 全量插件配置
"""
global plugin_config
for k in pconf:
plugin_config[k.lower()] = pconf[k]
def pconf(plugin_name: str) -> dict:
"""
根据插件名称获取配置
:param plugin_name: 插件名称
:return: 该插件的配置项
"""
return plugin_config.get(plugin_name.lower())
# 全局配置,用于存放全局生效的状态
global_config = {"admin_users": []}