# 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, 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 "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 # 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 # 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 "text_to_voice": "openai", # 语音合成引擎，支持openai,baidu,google,pytts(offline),ali,azure,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": []}