chatgpt-on-wechat/config.py

# encoding:utf-8

import json
import logging
import os
import pickle

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
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",
    "use_azure_chatgpt": False,  # 是否使用azure的chatgpt
    "azure_deployment_id": "",  # azure 模型部署名称
    # 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
    "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_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
    "trigger_by_self": False,  # 是否允许机器人触发
    "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
    # chatgpt会话参数
    "expires_in_seconds": 3600,  # 无操作会话的过期时间
    "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。",  # 人格描述
    "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": 60,  # 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
    # 语音设置
    "speech_recognition": False,  # 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": "baidu",  # 语音合成引擎，支持baidu,google,pytts(offline),azure
    # 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",
    # 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
    # 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
    # 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": "wx",  # 通道类型，支持：{wx,wxy,terminal,wechatmp,wechatmp_service}
    "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
}


class Config(dict):
    def __init__(self, d: dict = {}):
        super().__init__(d)
        # 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 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(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(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