v0.1

能跑但是没写部署教程，主题和记忆识别也没写完

src/plugins/chat/config.py

@@ -0,0 +1,109 @@
+from dataclasses import dataclass
+from typing import Dict, Any, Optional
+import os
+from nonebot.log import logger, default_format
+import logging
+import configparser  # 添加这行导入
+import tomli  # 添加这行导入
+
+# 禁用默认的日志输出
+# logger.remove()
+
+# # 只禁用 INFO 级别的日志输出到控制台
+# logging.getLogger('nonebot').handlers.clear()
+# console_handler = logging.StreamHandler()
+# console_handler.setLevel(logging.WARNING)  # 只输出 WARNING 及以上级别
+# logging.getLogger('nonebot').addHandler(console_handler)
+# logging.getLogger('nonebot').setLevel(logging.WARNING)
+
+@dataclass
+class BotConfig:
+    """机器人配置类"""
+    
+    # 基础配置
+    MONGODB_HOST: str = "127.0.0.1"
+    MONGODB_PORT: int = 27017
+    DATABASE_NAME: str = "MegBot"
+    
+    BOT_QQ: Optional[int] = 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
+    
+    read_allowed_groups = set()
+    talk_allowed_groups = set()
+    talk_frequency_down_groups = set()
+    
+    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）
+    
+    MODEL_R1_PROBABILITY: float = 0.3  # R1模型概率
+    
+    @classmethod
+    def load_config(cls, config_path: str = "bot_config.toml") -> "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)
+            
+            # 数据库配置
+            if "database" in toml_dict:
+                db_config = toml_dict["database"]
+                config.MONGODB_HOST = db_config.get("host", config.MONGODB_HOST)
+                config.MONGODB_PORT = db_config.get("port", config.MONGODB_PORT)
+                config.DATABASE_NAME = db_config.get("name", config.DATABASE_NAME)
+            
+            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)
+            
+            # 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)
+
+                
+            if "response" in toml_dict:
+                response_config = toml_dict["response"]
+                config.MODEL_R1_PROBABILITY = response_config.get("model_r1_probability", config.MODEL_R1_PROBABILITY)
+            
+            # 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)
+            
+            # 群组配置
+            if "groups" in toml_dict:
+                groups_config = toml_dict["groups"]
+                config.read_allowed_groups = set(groups_config.get("read_allowed", []))
+                config.talk_allowed_groups = set(groups_config.get("talk_allowed", []))
+                config.talk_frequency_down_groups = set(groups_config.get("talk_frequency_down", []))
+            
+            print(f"\033[1;32m成功加载配置文件: {config_path}\033[0m")
+                
+        return config 
+    
+global_config = BotConfig.load_config("./src/plugins/chat/bot_config.toml")
+
+from dotenv import load_dotenv
+current_dir = os.path.dirname(os.path.abspath(__file__))
+root_dir = os.path.abspath(os.path.join(current_dir, '..', '..', '..'))
+load_dotenv(os.path.join(root_dir, '.env'))
+
+@dataclass
+class LLMConfig:
+    """机器人配置类"""
+    # 基础配置
+    SILICONFLOW_API_KEY: str = None
+    SILICONFLOW_BASE_URL: str = None
+
+llm_config = LLMConfig()
+llm_config.SILICONFLOW_API_KEY = os.getenv('SILICONFLOW_KEY')
+llm_config.SILICONFLOW_BASE_URL = os.getenv('SILICONFLOW_BASE_URL')