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  1. # encoding:utf-8
  2. import json
  3. import logging
  4. import os
  5. import pickle
  6. import copy
  7. from common.log import logger
  8. # 将所有可用的配置项写在字典里, 请使用小写字母
  9. # 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
  10. available_setting = {
  11. # openai api配置
  12. "open_ai_api_key": "", # openai api key
  13. # openai apibase,当use_azure_chatgpt为true时,需要设置对应的api base
  14. "open_ai_api_base": "https://api.openai.com/v1",
  15. "proxy": "", # openai使用的代理
  16. # chatgpt模型, 当use_azure_chatgpt为true时,其名称为Azure上model deployment名称
  17. "model": "gpt-3.5-turbo", # 可选择: gpt-4o, 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
  18. "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,
  19. "use_azure_chatgpt": False, # 是否使用azure的chatgpt
  20. "azure_deployment_id": "", # azure 模型部署名称
  21. "azure_api_version": "", # azure api版本
  22. # Bot触发配置
  23. "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
  24. "single_chat_reply_prefix": "[bot] ", # 私聊时自动回复的前缀,用于区分真人
  25. "single_chat_reply_suffix": "", # 私聊时自动回复的后缀,\n 可以换行
  26. "group_chat_prefix": ["@bot"], # 群聊时包含该前缀则会触发机器人回复
  27. "group_chat_reply_prefix": "", # 群聊时自动回复的前缀
  28. "group_chat_reply_suffix": "", # 群聊时自动回复的后缀,\n 可以换行
  29. "group_chat_keyword": [], # 群聊时包含该关键词则会触发机器人回复
  30. "group_at_off": False, # 是否关闭群聊时@bot的触发
  31. "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
  32. "group_name_keyword_white_list": [], # 开启自动回复的群名称关键词列表
  33. "group_chat_in_one_session": ["ChatGPT测试群"], # 支持会话上下文共享的群名称
  34. "nick_name_black_list": [], # 用户昵称黑名单
  35. "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
  36. "trigger_by_self": False, # 是否允许机器人触发
  37. "text_to_image": "dall-e-2", # 图片生成模型,可选 dall-e-2, dall-e-3
  38. # Azure OpenAI dall-e-3 配置
  39. "dalle3_image_style": "vivid", # 图片生成dalle3的风格,可选有 vivid, natural
  40. "dalle3_image_quality": "hd", # 图片生成dalle3的质量,可选有 standard, hd
  41. # 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.
  42. "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
  43. "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
  44. "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
  45. "image_proxy": True, # 是否需要图片代理,国内访问LinkAI时需要
  46. "image_create_prefix": ["画", "看", "找"], # 开启图片回复的前缀
  47. "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
  48. "image_create_size": "256x256", # 图片大小,可选有 256x256, 512x512, 1024x1024 (dall-e-3默认为1024x1024)
  49. "group_chat_exit_group": False,
  50. # chatgpt会话参数
  51. "expires_in_seconds": 3600, # 无操作会话的过期时间
  52. # 人格描述
  53. "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。",
  54. "conversation_max_tokens": 1000, # 支持上下文记忆的最多字符数
  55. # chatgpt限流配置
  56. "rate_limit_chatgpt": 20, # chatgpt的调用频率限制
  57. "rate_limit_dalle": 50, # openai dalle的调用频率限制
  58. # chatgpt api参数 参考https://platform.openai.com/docs/api-reference/chat/create
  59. "temperature": 0.9,
  60. "top_p": 1,
  61. "frequency_penalty": 0,
  62. "presence_penalty": 0,
  63. "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
  64. "timeout": 120, # chatgpt重试超时时间,在这个时间内,将会自动重试
  65. # Baidu 文心一言参数
  66. "baidu_wenxin_model": "eb-instant", # 默认使用ERNIE-Bot-turbo模型
  67. "baidu_wenxin_api_key": "", # Baidu api key
  68. "baidu_wenxin_secret_key": "", # Baidu secret key
  69. # 讯飞星火API
  70. "xunfei_app_id": "", # 讯飞应用ID
  71. "xunfei_api_key": "", # 讯飞 API key
  72. "xunfei_api_secret": "", # 讯飞 API secret
  73. # claude 配置
  74. "claude_api_cookie": "",
  75. "claude_uuid": "",
  76. # claude api key
  77. "claude_api_key": "",
  78. # 通义千问API, 获取方式查看文档 https://help.aliyun.com/document_detail/2587494.html
  79. "qwen_access_key_id": "",
  80. "qwen_access_key_secret": "",
  81. "qwen_agent_key": "",
  82. "qwen_app_id": "",
  83. "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
  84. # 阿里灵积(通义新版sdk)模型api key
  85. "dashscope_api_key": "",
  86. # Google Gemini Api Key
  87. "gemini_api_key": "",
  88. # wework的通用配置
  89. "wework_smart": True, # 配置wework是否使用已登录的企业微信,False为多开
  90. # 语音设置
  91. "speech_recognition": True, # 是否开启语音识别
  92. "group_speech_recognition": False, # 是否开启群组语音识别
  93. "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
  94. "always_reply_voice": False, # 是否一直使用语音回复
  95. "voice_to_text": "openai", # 语音识别引擎,支持openai,baidu,google,azure
  96. "text_to_voice": "openai", # 语音合成引擎,支持openai,baidu,google,pytts(offline),ali,azure,elevenlabs,edge(online)
  97. "text_to_voice_model": "tts-1",
  98. "tts_voice_id": "alloy",
  99. # baidu 语音api配置, 使用百度语音识别和语音合成时需要
  100. "baidu_app_id": "",
  101. "baidu_api_key": "",
  102. "baidu_secret_key": "",
  103. # 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
  104. "baidu_dev_pid": 1536,
  105. # azure 语音api配置, 使用azure语音识别和语音合成时需要
  106. "azure_voice_api_key": "",
  107. "azure_voice_region": "japaneast",
  108. # elevenlabs 语音api配置
  109. "xi_api_key": "", # 获取ap的方法可以参考https://docs.elevenlabs.io/api-reference/quick-start/authentication
  110. "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”
  111. # 服务时间限制,目前支持itchat
  112. "chat_time_module": False, # 是否开启服务时间限制
  113. "chat_start_time": "00:00", # 服务开始时间
  114. "chat_stop_time": "24:00", # 服务结束时间
  115. # 翻译api
  116. "translate": "baidu", # 翻译api,支持baidu
  117. # baidu翻译api的配置
  118. "baidu_translate_app_id": "", # 百度翻译api的appid
  119. "baidu_translate_app_key": "", # 百度翻译api的秘钥
  120. # itchat的配置
  121. "hot_reload": False, # 是否开启热重载
  122. # wechaty的配置
  123. "wechaty_puppet_service_token": "", # wechaty的token
  124. # wechatmp的配置
  125. "wechatmp_token": "", # 微信公众平台的Token
  126. "wechatmp_port": 8080, # 微信公众平台的端口,需要端口转发到80或443
  127. "wechatmp_app_id": "", # 微信公众平台的appID
  128. "wechatmp_app_secret": "", # 微信公众平台的appsecret
  129. "wechatmp_aes_key": "", # 微信公众平台的EncodingAESKey,加密模式需要
  130. # wechatcom的通用配置
  131. "wechatcom_corp_id": "", # 企业微信公司的corpID
  132. # wechatcomapp的配置
  133. "wechatcomapp_token": "", # 企业微信app的token
  134. "wechatcomapp_port": 9898, # 企业微信app的服务端口,不需要端口转发
  135. "wechatcomapp_secret": "", # 企业微信app的secret
  136. "wechatcomapp_agent_id": "", # 企业微信app的agent_id
  137. "wechatcomapp_aes_key": "", # 企业微信app的aes_key
  138. # 飞书配置
  139. "feishu_port": 80, # 飞书bot监听端口
  140. "feishu_app_id": "", # 飞书机器人应用APP Id
  141. "feishu_app_secret": "", # 飞书机器人APP secret
  142. "feishu_token": "", # 飞书 verification token
  143. "feishu_bot_name": "", # 飞书机器人的名字
  144. # 钉钉配置
  145. "dingtalk_client_id": "", # 钉钉机器人Client ID
  146. "dingtalk_client_secret": "", # 钉钉机器人Client Secret
  147. "dingtalk_card_enabled": False,
  148. # chatgpt指令自定义触发词
  149. "clear_memory_commands": ["#清除记忆"], # 重置会话指令,必须以#开头
  150. # channel配置
  151. "channel_type": "", # 通道类型,支持:{wx,wxy,terminal,wechatmp,wechatmp_service,wechatcom_app,dingtalk}
  152. "subscribe_msg": "", # 订阅消息, 支持: wechatmp, wechatmp_service, wechatcom_app
  153. "debug": False, # 是否开启debug模式,开启后会打印更多日志
  154. "appdata_dir": "", # 数据目录
  155. # 插件配置
  156. "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
  157. # 是否使用全局插件配置
  158. "use_global_plugin_config": False,
  159. "max_media_send_count": 3, # 单次最大发送媒体资源的个数
  160. "media_send_interval": 1, # 发送图片的事件间隔,单位秒
  161. # 智谱AI 平台配置
  162. "zhipu_ai_api_key": "",
  163. "zhipu_ai_api_base": "https://open.bigmodel.cn/api/paas/v4",
  164. "moonshot_api_key": "",
  165. "moonshot_base_url": "https://api.moonshot.cn/v1/chat/completions",
  166. # LinkAI平台配置
  167. "use_linkai": False,
  168. "linkai_api_key": "",
  169. "linkai_app_code": "",
  170. "linkai_api_base": "https://api.link-ai.tech", # linkAI服务地址
  171. "Minimax_api_key": "",
  172. "Minimax_group_id": "",
  173. "Minimax_base_url": "",
  174. }
  175. class Config(dict):
  176. def __init__(self, d=None):
  177. super().__init__()
  178. if d is None:
  179. d = {}
  180. for k, v in d.items():
  181. self[k] = v
  182. # user_datas: 用户数据,key为用户名,value为用户数据,也是dict
  183. self.user_datas = {}
  184. def __getitem__(self, key):
  185. if key not in available_setting:
  186. raise Exception("key {} not in available_setting".format(key))
  187. return super().__getitem__(key)
  188. def __setitem__(self, key, value):
  189. if key not in available_setting:
  190. raise Exception("key {} not in available_setting".format(key))
  191. return super().__setitem__(key, value)
  192. def get(self, key, default=None):
  193. try:
  194. return self[key]
  195. except KeyError as e:
  196. return default
  197. except Exception as e:
  198. raise e
  199. # Make sure to return a dictionary to ensure atomic
  200. def get_user_data(self, user) -> dict:
  201. if self.user_datas.get(user) is None:
  202. self.user_datas[user] = {}
  203. return self.user_datas[user]
  204. def load_user_datas(self):
  205. try:
  206. with open(os.path.join(get_appdata_dir(), "user_datas.pkl"), "rb") as f:
  207. self.user_datas = pickle.load(f)
  208. logger.info("[Config] User datas loaded.")
  209. except FileNotFoundError as e:
  210. logger.info("[Config] User datas file not found, ignore.")
  211. except Exception as e:
  212. logger.info("[Config] User datas error: {}".format(e))
  213. self.user_datas = {}
  214. def save_user_datas(self):
  215. try:
  216. with open(os.path.join(get_appdata_dir(), "user_datas.pkl"), "wb") as f:
  217. pickle.dump(self.user_datas, f)
  218. logger.info("[Config] User datas saved.")
  219. except Exception as e:
  220. logger.info("[Config] User datas error: {}".format(e))
  221. config = Config()
  222. def drag_sensitive(config):
  223. try:
  224. if isinstance(config, str):
  225. conf_dict: dict = json.loads(config)
  226. conf_dict_copy = copy.deepcopy(conf_dict)
  227. for key in conf_dict_copy:
  228. if "key" in key or "secret" in key:
  229. if isinstance(conf_dict_copy[key], str):
  230. conf_dict_copy[key] = conf_dict_copy[key][0:3] + "*" * 5 + conf_dict_copy[key][-3:]
  231. return json.dumps(conf_dict_copy, indent=4)
  232. elif isinstance(config, dict):
  233. config_copy = copy.deepcopy(config)
  234. for key in config:
  235. if "key" in key or "secret" in key:
  236. if isinstance(config_copy[key], str):
  237. config_copy[key] = config_copy[key][0:3] + "*" * 5 + config_copy[key][-3:]
  238. return config_copy
  239. except Exception as e:
  240. logger.exception(e)
  241. return config
  242. return config
  243. def load_config():
  244. global config
  245. config_path = "./config.json"
  246. if not os.path.exists(config_path):
  247. logger.info("配置文件不存在,将使用config-template.json模板")
  248. config_path = "./config-template.json"
  249. config_str = read_file(config_path)
  250. logger.debug("[INIT] config str: {}".format(drag_sensitive(config_str)))
  251. # 将json字符串反序列化为dict类型
  252. config = Config(json.loads(config_str))
  253. # override config with environment variables.
  254. # 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.
  255. for name, value in os.environ.items():
  256. name = name.lower()
  257. if name in available_setting:
  258. logger.info("[INIT] override config by environ args: {}={}".format(name, value))
  259. try:
  260. config[name] = eval(value)
  261. except:
  262. if value == "false":
  263. config[name] = False
  264. elif value == "true":
  265. config[name] = True
  266. else:
  267. config[name] = value
  268. if config.get("debug", False):
  269. logger.setLevel(logging.DEBUG)
  270. logger.debug("[INIT] set log level to DEBUG")
  271. logger.info("[INIT] load config: {}".format(drag_sensitive(config)))
  272. config.load_user_datas()
  273. def get_root():
  274. return os.path.dirname(os.path.abspath(__file__))
  275. def read_file(path):
  276. with open(path, mode="r", encoding="utf-8") as f:
  277. return f.read()
  278. def conf():
  279. return config
  280. def get_appdata_dir():
  281. data_path = os.path.join(get_root(), conf().get("appdata_dir", ""))
  282. if not os.path.exists(data_path):
  283. logger.info("[INIT] data path not exists, create it: {}".format(data_path))
  284. os.makedirs(data_path)
  285. return data_path
  286. def subscribe_msg():
  287. trigger_prefix = conf().get("single_chat_prefix", [""])[0]
  288. msg = conf().get("subscribe_msg", "")
  289. return msg.format(trigger_prefix=trigger_prefix)
  290. # global plugin config
  291. plugin_config = {}
  292. def write_plugin_config(pconf: dict):
  293. """
  294. 写入插件全局配置
  295. :param pconf: 全量插件配置
  296. """
  297. global plugin_config
  298. for k in pconf:
  299. plugin_config[k.lower()] = pconf[k]
  300. def pconf(plugin_name: str) -> dict:
  301. """
  302. 根据插件名称获取配置
  303. :param plugin_name: 插件名称
  304. :return: 该插件的配置项
  305. """
  306. return plugin_config.get(plugin_name.lower())
  307. # 全局配置,用于存放全局生效的状态
  308. global_config = {"admin_users": []}