fixed

src/config/config.py

@@ -32,7 +32,7 @@ from src.config.official_configs import (
     PFCConfig,
     ModelConfig,
     ScheduleConfig,
-    GroupNicknameConfig,
+    GroupNicknameConfig
 )
 
 install(extra_lines=3)

src/config/official_configs.py

@@ -366,6 +366,9 @@ class ExperimentalConfig(ConfigBase):
     rename_person: bool = True
     """是否启用改名工具"""
 
+    enable_always_relative_history: bool = False
+    """聊天记录总是使用 relative 模式"""
+
 
 @dataclass
 class ScheduleConfig(ConfigBase):
@@ -527,14 +530,14 @@ class ModelConfig(ConfigBase):
     tool_use: dict[str, Any] = field(default_factory=lambda: {})
     """工具使用模型配置"""
 
-    nickname_mapping: dict[str, str] = field(default_factory=lambda: {})
+    nickname_mapping: dict[str, Any] = field(default_factory=lambda: {})
     """绰号映射LLM配置"""
 
-    scheduler_all: dict[str, str] = field(default_factory=lambda: {})
+    scheduler_all: dict[str, Any] = field(default_factory=lambda: {})
     """全局日程LLM配置"""
 
-    scheduler_doing: dict[str, str] = field(default_factory=lambda: {})
+    scheduler_doing: dict[str, Any] = field(default_factory=lambda: {})
     """当前活动日程LLM配置"""
 
-    PFC_relationship_eval: dict[str, str] = field(default_factory=lambda: {})
+    PFC_relationship_eval: dict[str, Any] = field(default_factory=lambda: {})
     """PFC关系评估LLM配置"""

src/experimental/Legacy_HFC/heartflow_prompt_builder.py

@@ -487,17 +487,14 @@ class PromptBuilder:
         keywords_reaction_prompt = ""
         keywords_reaction_prompt = ""
         for rule in global_config.keyword_reaction.rules:
-            if rule.get("enable", False):
+            if rule.enable:
-                if any(keyword in message_txt.lower() for keyword in rule.get("keywords", [])):
+                if any(keyword in message_txt for keyword in rule.keywords):
-                    logger.info(
+                    logger.info(f"检测到以下关键词之一：{rule.keywords}，触发反应：{rule.reaction}")
-                        f"检测到以下关键词之一：{rule.get('keywords', [])}，触发反应：{rule.get('reaction', '')}"
+                    keywords_reaction_prompt += f"{rule.reaction}，"
-                    )
-                    keywords_reaction_prompt += rule.get("reaction", "") + "，"
                 else:
-                    for pattern in rule.get("regex", []):
+                    for pattern in rule.regex:
-                        result = pattern.search(message_txt)
+                        if result := pattern.search(message_txt):
-                        if result:
+                            reaction = rule.reaction
-                            reaction = rule.get("reaction", "")
                             for name, content in result.groupdict().items():
                                 reaction = reaction.replace(f"[{name}]", content)
                             logger.info(f"匹配到以下正则表达式：{pattern}，触发反应：{reaction}")

src/plugins/group_nickname/nickname_manager.py

@@ -103,8 +103,7 @@ class NicknameManager:
                 return
 
             logger.info("正在初始化 NicknameManager 组件...")
-            self.config = global_config
+            self.is_enabled = global_config.group_nickname.enable_nickname_mapping
-            self.is_enabled = self.config.enable_nickname_mapping
 
             # 数据库处理器
             person_info_collection = getattr(db, "person_info", None)
@@ -117,7 +116,7 @@ class NicknameManager:
             self.llm_mapper: Optional[LLMRequest] = None
             if self.is_enabled:
                 try:
-                    model_config = self.config.llm_nickname_mapping
+                    model_config = global_config.model.nickname_mapping
                     if model_config and model_config.get("name"):
                         self.llm_mapper = LLMRequest(
                             model=model_config,
@@ -139,12 +138,12 @@ class NicknameManager:
                     self.is_enabled = False
 
             # 队列和线程
-            self.queue_max_size = getattr(self.config, "nickname_queue_max_size", 100)
+            self.queue_max_size = global_config.group_nickname.nickname_queue_max_size
             # 使用 asyncio.Queue
             self.nickname_queue: asyncio.Queue = asyncio.Queue(maxsize=self.queue_max_size)
             self._stop_event = threading.Event()  # stop_event 仍然使用 threading.Event，因为它是由另一个线程设置的
             self._nickname_thread: Optional[threading.Thread] = None
-            self.sleep_interval = getattr(self.config, "nickname_process_sleep_interval", 5)  # 超时时间
+            self.sleep_interval = global_config.group_nickname.nickname_process_sleep_interval  # 超时时间
 
             self._initialized = True
             logger.info("NicknameManager 初始化完成。")
@@ -222,7 +221,7 @@ class NicknameManager:
         log_prefix = f"[{current_chat_stream.stream_id}]"
         try:
             # 1. 获取历史记录
-            history_limit = getattr(self.config, "nickname_analysis_history_limit", 30)
+            history_limit = global_config.group_nickname.nickname_analysis_history_limit
             history_messages = get_raw_msg_before_timestamp_with_chat(
                 chat_id=current_chat_stream.stream_id,
                 timestamp=time.time(),
@@ -470,7 +469,7 @@ class NicknameManager:
     def _filter_llm_results(self, original_data: Dict[str, str], user_name_map: Dict[str, str]) -> Dict[str, str]:
         """过滤 LLM 返回的绰号映射结果。"""
         filtered_data = {}
-        bot_qq_str = str(self.config.BOT_QQ) if hasattr(self.config, "BOT_QQ") else None
+        bot_qq_str = global_config.bot.qq_account if global_config.bot.qq_account else None
 
         for user_id, nickname in original_data.items():
             if not isinstance(user_id, str):

template/bot_config_template.toml

@@ -18,7 +18,7 @@ nickname = "麦麦"
 alias_names = ["麦叠", "牢麦"] #该选项还在调试中，暂时未生效
 
 [chat_target]
-talk_allowed = [
+talk_allowed_groups = [
     123,
     123,
 ]  #可以回复消息的群号码
@@ -55,8 +55,7 @@ weight = "50" # 体重（单位kg）
 appearance = "用一句或几句话描述外貌特征" # 外貌特征 该选项还在调试中，暂时未生效
 
 [schedule]
-enable_schedule_gen = true # 是否启用日程表
+enable = true # 是否启用日程表
-enable_schedule_interaction = true # 日程表是否影响回复模式
 prompt_schedule_gen = "用几句话描述描述性格特点或行动规律，这个特征会用来生成日程表"
 schedule_doing_update_interval = 900 # 日程表更新间隔 单位秒
 schedule_temperature = 0.1 # 日程表温度，建议0.1-0.5
@@ -199,20 +198,20 @@ talk_allowed_private = [] # 可以回复消息的QQ号
 rename_person = true  # 是否启用改名工具，可以让麦麦对唯一名进行更改，可能可以更拟人地称呼他人，但是也可能导致记忆混淆的问题
 
 [pfc]
-enable_pfc_chatting = true # 是否启用PFC聊天，该功能仅作用于私聊，与回复模式独立
+enable = true # 是否启用PFC聊天，该功能仅作用于私聊，与回复模式独立
 pfc_message_buffer_size = 2  # PFC 聊天消息缓冲数量，有利于使聊天节奏更加紧凑流畅，请根据实际 LLM 响应速度进行调整，默认2条
 pfc_recent_history_display_count = 18  # PFC 对话最大可见上下文
 
-[[pfc.checker]]
+# pfc.checker
 enable_pfc_reply_checker = true # 是否启用 PFC 的回复检查器
 pfc_max_reply_attempts = 3  # 发言最多尝试次数
 pfc_max_chat_history_for_checker = 30  # checker聊天记录最大可见上文长度
 
-[[pfc.emotion]]
+# pfc.emotion
 pfc_emotion_update_intensity = 0.6  # 情绪更新强度
 pfc_emotion_history_count = 5  # 情绪更新最大可见上下文长度
 
-[[pfc.relationship]]
+# pfc.relationship
 pfc_relationship_incremental_interval = 10  # 关系值增值强度
 pfc_relationship_incremental_msg_count = 10  # 会话中，关系值判断最大可见上下文
 pfc_relationship_incremental_default_change = 1.0  # 会话中，关系值默认更新值（当 llm 返回错误时默认采用该值）
@@ -221,10 +220,10 @@ pfc_relationship_final_msg_count = 30  # 会话结束时，关系值判断最大
 pfc_relationship_final_default_change =5.0  # 会话结束时，关系值默认更新值
 pfc_relationship_final_max_change = 50.0  # 会话结束时，关系值最大可变值
 
-[[pfc.fallback]]
+# pfc.fallback
 pfc_historical_fallback_exclude_seconds = 45 # pfc 翻看聊天记录排除最近时长
 
-[[pfc.idle_chat]]
+# pfc.idle_chat
 enable_idle_chat = true # 是否启用 pfc 主动发言
 idle_check_interval = 10  # 检查间隔，10分钟检查一次
 min_cooldown = 7200      # 最短冷却时间，2小时 (7200秒)
@@ -319,6 +318,7 @@ provider = "SILICONFLOW"
 temp = 0.3
 pri_in = 2
 pri_out = 8
+max_tokens = 512
 
 #PFC聊天模型
 [model.pfc_chat]
@@ -329,7 +329,7 @@ pri_in = 2
 pri_out = 8
 
 #绰号映射生成模型
-[model.llm_nickname_mapping]
+[model.nickname_mapping]
 name = "Qwen/Qwen2.5-32B-Instruct"
 provider = "SILICONFLOW"
 temp = 0.7
@@ -337,7 +337,7 @@ pri_in = 1.26
 pri_out = 1.26
 
 #日程模型
-[model.llm_scheduler_all]
+[model.scheduler_all]
 name = "deepseek-ai/DeepSeek-V3"
 provider = "SILICONFLOW"
 temp = 0.3
@@ -345,7 +345,7 @@ pri_in = 2
 pri_out = 8
 
 #在干嘛模型
-[model.llm_scheduler_doing]
+[model.scheduler_doing]
 name = "deepseek-ai/DeepSeek-V3"
 provider = "SILICONFLOW"
 temp = 0.3
@@ -353,7 +353,7 @@ pri_in = 2
 pri_out = 8
 
 # PFC 关系评估LLM
-[model.llm_PFC_relationship_eval]
+[model.PFC_relationship_eval]
 name = "deepseek-ai/DeepSeek-V3"
 provider = "SILICONFLOW"
 temp = 0.4