from dataclasses import dataclass, field from typing import Dict, Any, Optional, Set import os import configparser import tomli import sys from loguru import logger from nonebot import get_driver @dataclass class BotConfig: """机器人配置类""" BOT_QQ: Optional[int] = 1 BOT_NICKNAME: Optional[str] = None # 消息处理相关配置 MIN_TEXT_LENGTH: int = 2 # 最小处理文本长度 MAX_CONTEXT_SIZE: int = 15 # 上下文最大消息数 emoji_chance: float = 0.2 # 发送表情包的基础概率 ENABLE_PIC_TRANSLATE: bool = True # 是否启用图片翻译 talk_allowed_groups = set() talk_frequency_down_groups = set() ban_user_id = set() build_memory_interval: int = 30 # 记忆构建间隔（秒） forget_memory_interval: int = 300 # 记忆遗忘间隔（秒） EMOJI_CHECK_INTERVAL: int = 120 # 表情包检查间隔（分钟） EMOJI_REGISTER_INTERVAL: int = 10 # 表情包注册间隔（分钟） ban_words = set() # 模型配置 llm_reasoning: Dict[str, str] = field(default_factory=lambda: {}) llm_reasoning_minor: Dict[str, str] = field(default_factory=lambda: {}) llm_normal: Dict[str, str] = field(default_factory=lambda: {}) llm_normal_minor: Dict[str, str] = field(default_factory=lambda: {}) embedding: Dict[str, str] = field(default_factory=lambda: {}) vlm: Dict[str, str] = field(default_factory=lambda: {}) rerank: Dict[str, str] = field(default_factory=lambda: {}) # 主题提取配置 topic_extract: str = 'snownlp' # 只支持jieba,snownlp,llm llm_topic_extract: Dict[str, str] = field(default_factory=lambda: {}) API_USING: str = "siliconflow" # 使用的API API_PAID: bool = False # 是否使用付费API MODEL_R1_PROBABILITY: float = 0.8 # R1模型概率 MODEL_V3_PROBABILITY: float = 0.1 # V3模型概率 MODEL_R1_DISTILL_PROBABILITY: float = 0.1 # R1蒸馏模型概率 enable_advance_output: bool = False # 是否启用高级输出 enable_kuuki_read: bool = True # 是否启用读空气功能 # 默认人设 PROMPT_PERSONALITY=[ "曾经是一个学习地质的女大学生，现在学习心理学和脑科学，你会刷贴吧", "是一个女大学生，你有黑色头发，你会刷小红书" ] PROMPT_SCHEDULE_GEN="一个曾经学习地质,现在学习心理学和脑科学的女大学生，喜欢刷qq，贴吧，知乎和小红书" @staticmethod def get_config_dir() -> str: """获取配置文件目录""" current_dir = os.path.dirname(os.path.abspath(__file__)) root_dir = os.path.abspath(os.path.join(current_dir, '..', '..', '..')) config_dir = os.path.join(root_dir, 'config') if not os.path.exists(config_dir): os.makedirs(config_dir) return config_dir @classmethod def load_config(cls, config_path: str = None) -> "BotConfig": """从TOML配置文件加载配置""" config = cls() if os.path.exists(config_path): with open(config_path, "rb") as f: toml_dict = tomli.load(f) if 'personality' in toml_dict: personality_config=toml_dict['personality'] personality=personality_config.get('prompt_personality') if len(personality) >= 2: logger.info(f"载入自定义人格:{personality}") config.PROMPT_PERSONALITY=personality_config.get('prompt_personality',config.PROMPT_PERSONALITY) logger.info(f"载入自定义日程prompt:{personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)}") config.PROMPT_SCHEDULE_GEN=personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN) if "emoji" in toml_dict: emoji_config = toml_dict["emoji"] config.EMOJI_CHECK_INTERVAL = emoji_config.get("check_interval", config.EMOJI_CHECK_INTERVAL) config.EMOJI_REGISTER_INTERVAL = emoji_config.get("register_interval", config.EMOJI_REGISTER_INTERVAL) if "cq_code" in toml_dict: cq_code_config = toml_dict["cq_code"] config.ENABLE_PIC_TRANSLATE = cq_code_config.get("enable_pic_translate", config.ENABLE_PIC_TRANSLATE) # 机器人基础配置 if "bot" in toml_dict: bot_config = toml_dict["bot"] bot_qq = bot_config.get("qq") config.BOT_QQ = int(bot_qq) config.BOT_NICKNAME = bot_config.get("nickname", config.BOT_NICKNAME) if "response" in toml_dict: response_config = toml_dict["response"] config.MODEL_R1_PROBABILITY = response_config.get("model_r1_probability", config.MODEL_R1_PROBABILITY) config.MODEL_V3_PROBABILITY = response_config.get("model_v3_probability", config.MODEL_V3_PROBABILITY) config.MODEL_R1_DISTILL_PROBABILITY = response_config.get("model_r1_distill_probability", config.MODEL_R1_DISTILL_PROBABILITY) config.API_USING = response_config.get("api_using", config.API_USING) config.API_PAID = response_config.get("api_paid", config.API_PAID) # 加载模型配置 if "model" in toml_dict: model_config = toml_dict["model"] if "llm_reasoning" in model_config: config.llm_reasoning = model_config["llm_reasoning"] if "llm_reasoning_minor" in model_config: config.llm_reasoning_minor = model_config["llm_reasoning_minor"] if "llm_normal" in model_config: config.llm_normal = model_config["llm_normal"] config.llm_topic_extract = config.llm_normal if "llm_normal_minor" in model_config: config.llm_normal_minor = model_config["llm_normal_minor"] if "vlm" in model_config: config.vlm = model_config["vlm"] if "embedding" in model_config: config.embedding = model_config["embedding"] if "rerank" in model_config: config.rerank = model_config["rerank"] if 'topic' in toml_dict: topic_config=toml_dict['topic'] if 'topic_extract' in topic_config: config.topic_extract=topic_config.get('topic_extract',config.topic_extract) logger.info(f"载入自定义主题提取为{config.topic_extract}") if config.topic_extract=='llm' and 'llm_topic' in topic_config: config.llm_topic_extract=topic_config['llm_topic'] logger.info(f"载入自定义主题提取模型为{config.llm_topic_extract['name']}") # 消息配置 if "message" in toml_dict: msg_config = toml_dict["message"] config.MIN_TEXT_LENGTH = msg_config.get("min_text_length", config.MIN_TEXT_LENGTH) config.MAX_CONTEXT_SIZE = msg_config.get("max_context_size", config.MAX_CONTEXT_SIZE) config.emoji_chance = msg_config.get("emoji_chance", config.emoji_chance) config.ban_words=msg_config.get("ban_words",config.ban_words) if "memory" in toml_dict: memory_config = toml_dict["memory"] config.build_memory_interval = memory_config.get("build_memory_interval", config.build_memory_interval) config.forget_memory_interval = memory_config.get("forget_memory_interval", config.forget_memory_interval) # 群组配置 if "groups" in toml_dict: groups_config = toml_dict["groups"] config.talk_allowed_groups = set(groups_config.get("talk_allowed", [])) config.talk_frequency_down_groups = set(groups_config.get("talk_frequency_down", [])) config.ban_user_id = set(groups_config.get("ban_user_id", [])) if "others" in toml_dict: others_config = toml_dict["others"] config.enable_advance_output = others_config.get("enable_advance_output", config.enable_advance_output) config.enable_kuuki_read = others_config.get("enable_kuuki_read", config.enable_kuuki_read) logger.success(f"成功加载配置文件: {config_path}") return config # 获取配置文件路径 bot_config_floder_path = BotConfig.get_config_dir() print(f"正在品鉴配置文件目录: {bot_config_floder_path}") bot_config_path = os.path.join(bot_config_floder_path, "bot_config_dev.toml") if not os.path.exists(bot_config_path): # 如果开发环境配置文件不存在，则使用默认配置文件 bot_config_path = os.path.join(bot_config_floder_path, "bot_config.toml") logger.info("使用bot配置文件") else: logger.info("已找到开发bot配置文件") global_config = BotConfig.load_config(config_path=bot_config_path) if not global_config.enable_advance_output: logger.remove() pass