修改配置文件

src/chat/heart_flow/heartFC_chat.py

@@ -109,7 +109,7 @@ class HeartFChatting:
 
         self.last_read_time = time.time() - 10
         
-        
+        self.talk_threshold = global_config.chat.talk_value
         
         self.no_reply_until_call = False
 
@@ -172,6 +172,16 @@ class HeartFChatting:
             f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒"  # type: ignore
             + (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
         )
+        
+    def get_talk_threshold(self):
+        talk_value = global_config.chat.talk_value
+        # 处理talk_value：取整数部分和小数部分
+        base_value = int(talk_value)
+        probability = talk_value - base_value
+        # 根据概率决定是否+1
+        think_len = base_value + 1 if random.random() < probability else base_value
+        self.talk_threshold = think_len
+        logger.info(f"{self.log_prefix} 思考频率阈值: {self.talk_threshold}")
 
     async def _loopbody(self):
         recent_messages_list = message_api.get_messages_by_time_in_chat(
@@ -184,7 +194,7 @@ class HeartFChatting:
             filter_command=True,
         )
 
-        if recent_messages_list:
+        if len(recent_messages_list) >= self.talk_threshold:
             
             # !处理no_reply_until_call逻辑
             if self.no_reply_until_call:
@@ -203,6 +213,7 @@ class HeartFChatting:
             await self._observe(
                 recent_messages_list=recent_messages_list,
             )
+            self.get_talk_threshold()
         else:
             # Normal模式：消息数量不足，等待
             await asyncio.sleep(0.2)

src/chat/heart_flow/heartflow_message_processor.py

@@ -6,7 +6,6 @@ import traceback
 from typing import Tuple, TYPE_CHECKING
 
 from src.config.config import global_config
-from src.chat.memory_system.Hippocampus import hippocampus_manager
 from src.chat.message_receive.message import MessageRecv
 from src.chat.message_receive.storage import MessageStorage
 from src.chat.heart_flow.heartflow import heartflow
@@ -38,16 +37,16 @@ async def _calculate_interest(message: MessageRecv) -> Tuple[float, list[str]]:
 
     is_mentioned, is_at, reply_probability_boost = is_mentioned_bot_in_message(message)
     interested_rate = 0.0
-
+    keywords = []
-    with Timer("记忆激活"):
+    # with Timer("记忆激活"):
-        interested_rate, keywords, keywords_lite = await hippocampus_manager.get_activate_from_text(
+    #     interested_rate, keywords, keywords_lite = await hippocampus_manager.get_activate_from_text(
-            message.processed_plain_text,
+    #         message.processed_plain_text,
-            max_depth=4,
+    #         max_depth=4,
-            fast_retrieval=global_config.chat.interest_rate_mode == "fast",
+    #         fast_retrieval=global_config.chat.interest_rate_mode == "fast",
-        )
+    #     )
-        message.key_words = keywords
+    #     message.key_words = keywords
-        message.key_words_lite = keywords_lite
+    #     message.key_words_lite = keywords_lite
-        logger.debug(f"记忆激活率: {interested_rate:.2f}, 关键词: {keywords}")
+    #     logger.debug(f"记忆激活率: {interested_rate:.2f}, 关键词: {keywords}")
 
     text_len = len(message.processed_plain_text)
     # 根据文本长度分布调整兴趣度，采用分段函数实现更精确的兴趣度计算

src/chat/replyer/default_generator.py

@@ -25,7 +25,7 @@ from src.chat.utils.chat_message_builder import (
     replace_user_references,
 )
 from src.chat.express.expression_selector import expression_selector
-from src.chat.memory_system.memory_activator import MemoryActivator
+# from src.chat.memory_system.memory_activator import MemoryActivator
 from src.mood.mood_manager import mood_manager
 from src.person_info.person_info import Person, is_person_known
 from src.plugin_system.base.component_types import ActionInfo, EventType
@@ -143,7 +143,7 @@ class DefaultReplyer:
         self.chat_stream = chat_stream
         self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_stream.stream_id)
         self.heart_fc_sender = UniversalMessageSender()
-        self.memory_activator = MemoryActivator()
+        # self.memory_activator = MemoryActivator()
 
         from src.plugin_system.core.tool_use import ToolExecutor  # 延迟导入ToolExecutor，不然会循环依赖
 
@@ -1019,9 +1019,6 @@ class DefaultReplyer:
     async def llm_generate_content(self, prompt: str):
         with Timer("LLM生成", {}):  # 内部计时器，可选保留
             # 直接使用已初始化的模型实例
-            logger.info(f"使用模型集生成回复: {', '.join(map(str, self.express_model.model_for_task.model_list))}")
-
-            logger.info(f"\n{prompt}\n")
 
             if global_config.debug.show_prompt:
                 logger.info(f"\n{prompt}\n")

src/config/config.py

@@ -18,7 +18,6 @@ from src.config.official_configs import (
     ExpressionConfig,
     ChatConfig,
     EmojiConfig,
-    MemoryConfig,
     MoodConfig,
     KeywordReactionConfig,
     ChineseTypoConfig,
@@ -347,7 +346,6 @@ class Config(ConfigBase):
     message_receive: MessageReceiveConfig
     emoji: EmojiConfig
     expression: ExpressionConfig
-    memory: MemoryConfig
     mood: MoodConfig
     keyword_reaction: KeywordReactionConfig
     chinese_typo: ChineseTypoConfig

src/config/official_configs.py

@@ -77,6 +77,9 @@ class ChatConfig(ConfigBase):
 
     talk_frequency: float = 0.5
     """回复频率阈值"""
+    
+    talk_value: float = 1
+    """思考频率"""
 
     # 合并后的时段频率配置
     talk_frequency_adjust: list[list[str]] = field(default_factory=lambda: [])
@@ -321,26 +324,6 @@ class EmojiConfig(ConfigBase):
     """表情包过滤要求"""
 
 
-@dataclass
-class MemoryConfig(ConfigBase):
-    """记忆配置类"""
-
-    enable_memory: bool = True
-    """是否启用记忆系统"""
-
-    forget_memory_interval: int = 1500
-    """记忆遗忘间隔（秒）"""
-
-    memory_forget_time: int = 24
-    """记忆遗忘时间（小时）"""
-
-    memory_forget_percentage: float = 0.01
-    """记忆遗忘比例"""
-
-    memory_ban_words: list[str] = field(default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"])
-    """不允许记忆的词列表"""
-
-
 @dataclass
 class MoodConfig(ConfigBase):
     """情绪配置类"""

src/main.py

@@ -23,10 +23,6 @@ from src.plugin_system.core.plugin_manager import plugin_manager
 # 导入消息API和traceback模块
 from src.common.message import get_global_api
 
-# 条件导入记忆系统
-if global_config.memory.enable_memory:
-    from src.chat.memory_system.Hippocampus import hippocampus_manager
-
 # 插件系统现在使用统一的插件加载器
 
 install(extra_lines=3)
@@ -36,10 +32,6 @@ logger = get_logger("main")
 
 class MainSystem:
     def __init__(self):
-        # 根据配置条件性地初始化记忆系统
-        self.hippocampus_manager = None
-        if global_config.memory.enable_memory:
-            self.hippocampus_manager = hippocampus_manager
 
         # 使用消息API替代直接的FastAPI实例
         self.app: MessageServer = get_global_api()
@@ -101,13 +93,13 @@ class MainSystem:
 
         logger.info("聊天管理器初始化成功")
 
-        # 根据配置条件性地初始化记忆系统
+        # # 根据配置条件性地初始化记忆系统
-        if global_config.memory.enable_memory:
+        # if global_config.memory.enable_memory:
-            if self.hippocampus_manager:
+        #     if self.hippocampus_manager:
-                self.hippocampus_manager.initialize()
+        #         self.hippocampus_manager.initialize()
-                logger.info("记忆系统初始化成功")
+        #         logger.info("记忆系统初始化成功")
-        else:
+        # else:
-            logger.info("记忆系统已禁用，跳过初始化")
+        #     logger.info("记忆系统已禁用，跳过初始化")
 
         # await asyncio.sleep(0.5) #防止logger输出飞了
 
@@ -139,14 +131,14 @@ class MainSystem:
             ]
 
             # 根据配置条件性地添加记忆系统相关任务
-            if global_config.memory.enable_memory and self.hippocampus_manager:
+            # if global_config.memory.enable_memory and self.hippocampus_manager:
-                tasks.extend(
+            #     tasks.extend(
-                    [
+            #         [
-                        # 移除记忆构建的定期调用，改为在heartFC_chat.py中调用
+            #             # 移除记忆构建的定期调用，改为在heartFC_chat.py中调用
-                        # self.build_memory_task(),
+            #             # self.build_memory_task(),
-                        self.forget_memory_task(),
+            #             self.forget_memory_task(),
-                    ]
+            #         ]
-                )
+            #     )
 
             await asyncio.gather(*tasks)
 

template/bot_config_template.toml

@@ -1,5 +1,5 @@
 [inner]
-version = "6.9.0"
+version = "6.10.1"
 
 #----以下是给开发人员阅读的，如果你只是部署了麦麦，不需要阅读----
 #如果你想要修改配置文件，请递增version的值
@@ -50,48 +50,9 @@ expression_groups = [
 
 
 [chat] #麦麦的聊天设置
-talk_frequency = 0.5
+talk_value = 1.5 
-# 麦麦活跃度，越高，麦麦越容易回复，范围0-1
-focus_value = 0.5 
-# 麦麦的专注度，越高越容易持续连续对话，可能消耗更多token, 范围0-1
-
-mentioned_bot_reply = 1 # 提及时,回复概率增幅，1为100%回复，0为不额外增幅
-at_bot_inevitable_reply = 1 # at时,回复概率增幅，1为100%回复，0为不额外增幅
-
 max_context_size = 20 # 上下文长度
 
-planner_size = 3.5 # 副规划器大小，越小，麦麦的动作执行能力越精细，但是消耗更多token，调大可以缓解429类错误
-
-focus_value_adjust = [
-    ["", "8:00,1", "12:00,0.8", "18:00,1", "01:00,0.3"],
-    ["qq:114514:group", "12:20,0.6", "16:10,0.5", "20:10,0.8", "00:10,0.3"],
-    ["qq:1919810:private", "8:20,0.5", "12:10,0.8", "20:10,1", "00:10,0.2"]
-]
-
-talk_frequency_adjust = [
-    ["", "8:00,0.5", "12:00,0.6", "18:00,0.8", "01:00,0.3"],
-    ["qq:114514:group", "12:20,0.3", "16:10,0.5", "20:10,0.4", "00:10,0.1"],
-    ["qq:1919810:private", "8:20,0.3", "12:10,0.4", "20:10,0.5", "00:10,0.1"]
-]
-# 基于聊天流的个性化活跃度和专注度配置
-# 格式：[["platform:chat_id:type", "HH:MM,frequency", "HH:MM,frequency", ...], ...]
-
-# 全局配置示例：
-# [["", "8:00,1", "12:00,2", "18:00,1.5", "00:00,0.5"]]
-
-# 特定聊天流配置示例：
-# [
-#     ["", "8:00,1", "12:00,1.2", "18:00,1.5", "01:00,0.6"],  # 全局默认配置
-#     ["qq:1026294844:group", "12:20,1", "16:10,2", "20:10,1", "00:10,0.3"],  # 特定群聊配置
-#     ["qq:729957033:private", "8:20,1", "12:10,2", "20:10,1.5", "00:10,0.2"]  # 特定私聊配置
-# ]
-
-# 说明：
-# - 当第一个元素为空字符串""时，表示全局默认配置
-# - 当第一个元素为"platform:id:type"格式时，表示特定聊天流配置
-# - 后续元素是"时间,频率"格式，表示从该时间开始使用该活跃度，直到下一个时间点
-# - 优先级：特定聊天流配置 > 全局配置 > 默认 talk_frequency
-
 [relationship]
 enable_relationship = true # 是否启用关系系统
 
@@ -112,15 +73,6 @@ steal_emoji = true # 是否偷取表情包，让麦麦可以将一些表情包
 content_filtration = false  # 是否启用表情包过滤，只有符合该要求的表情包才会被保存
 filtration_prompt = "符合公序良俗" # 表情包过滤要求，只有符合该要求的表情包才会被保存
 
-[memory]
-enable_memory = true # 是否启用记忆系统
-forget_memory_interval = 1500 # 记忆遗忘间隔 单位秒   间隔越低，麦麦遗忘越频繁，记忆更精简，但更难学习
-memory_forget_time = 48 #多长时间后的记忆会被遗忘 单位小时
-memory_forget_percentage = 0.008 # 记忆遗忘比例 控制记忆遗忘程度 越大遗忘越多 建议保持默认
-
-#不希望记忆的词，已经记忆的不会受到影响，需要手动清理
-memory_ban_words = [ "表情包", "图片", "回复", "聊天记录" ]
-
 [voice]
 enable_asr = false # 是否启用语音识别，启用后麦麦可以识别语音消息，启用该功能需要配置语音识别模型[model.voice]s