fix：修复私聊bug

src/chat/focus_chat/expressors/default_expressor.py

@@ -358,14 +358,18 @@ class DefaultExpressor:
             )
         else:  # Private chat
             template_name = "default_expressor_private_prompt"
+            chat_target_1 = "你正在和人私聊"
             prompt = await global_prompt_manager.format_prompt(
                 template_name,
-                sender_name=effective_sender_name,  # Used in private template
-                chat_talking_prompt=chat_talking_prompt,
+                style_habbits=style_habbits_str,
+                grammar_habbits=grammar_habbits_str,
+                chat_target=chat_target_1,
+                chat_info=chat_talking_prompt,
                 bot_name=global_config.bot.nickname,
-                prompt_personality=prompt_personality,
+                prompt_personality="",
                 reason=reason,
-                moderation_prompt=await global_prompt_manager.get_prompt_async("moderation_prompt"),
+                in_mind_reply=in_mind_reply,
+                target_message=target_message,
             )
 
         return prompt

src/chat/focus_chat/heartFC_chat.py

@@ -54,7 +54,7 @@ CONSECUTIVE_NO_REPLY_THRESHOLD = 3  # 连续不回复的阈值
 logger = get_logger("hfc")  # Logger Name Changed
 
 # 设定处理器超时时间（秒）
-PROCESSOR_TIMEOUT = 10
+PROCESSOR_TIMEOUT = 20
 
 
 async def _handle_cycle_delay(action_taken_this_cycle: bool, cycle_start_time: float, log_prefix: str):

src/chat/focus_chat/info_processors/action_processor.py

@@ -137,9 +137,9 @@ class ActionProcessor(BaseProcessor):
         # 检查no_reply比例
         print(f"no_reply_count: {no_reply_count}, len(recent_cycles): {len(recent_cycles)}")
         # print(1111111111111111111111111111111111111111111111111111111111111111111111111111111111111111)
-        if len(recent_cycles) >= (5 * global_config.focus_chat.exit_focus_threshold) and (
+        if len(recent_cycles) >= (5 * global_config.chat.exit_focus_threshold) and (
             no_reply_count / len(recent_cycles)
-        ) >= (0.8 * global_config.focus_chat.exit_focus_threshold):
+        ) >= (0.8 * global_config.chat.exit_focus_threshold):
             if global_config.chat.chat_mode == "auto":
                 result["add"].append("exit_focus_chat")
                 result["remove"].append("no_reply")

src/chat/normal_chat/normal_chat.py

@@ -472,8 +472,8 @@ class NormalChat:
             return  # 如果没有设置回调函数，直接返回
         current_time = time.time()
 
-        time_threshold = 120 / global_config.focus_chat.auto_focus_threshold
-        reply_threshold = 6 * global_config.focus_chat.auto_focus_threshold
+        time_threshold = 120 / global_config.chat.auto_focus_threshold
+        reply_threshold = 6 * global_config.chat.auto_focus_threshold
 
         one_minute_ago = current_time - time_threshold
 

src/config/official_configs.py

@@ -59,6 +59,12 @@ class ChatConfig(ConfigBase):
 
     chat_mode: str = "normal"
     """聊天模式"""
+    
+    auto_focus_threshold: float = 1.0
+    """自动切换到专注聊天的阈值，越低越容易进入专注聊天"""
+
+    exit_focus_threshold: float = 1.0
+    """自动退出专注聊天的阈值，越低越容易退出专注聊天"""
 
 
 @dataclass
@@ -123,11 +129,7 @@ class NormalChatConfig(ConfigBase):
 class FocusChatConfig(ConfigBase):
     """专注聊天配置类"""
 
-    auto_focus_threshold: float = 1.0
-    """自动切换到专注聊天的阈值，越低越容易进入专注聊天"""
 
-    exit_focus_threshold: float = 1.0
-    """自动退出专注聊天的阈值，越低越容易退出专注聊天"""
 
     observation_context_size: int = 12
     """可观察到的最长上下文大小，超过这个值的上下文会被压缩"""

template/bot_config_template.toml

@@ -44,6 +44,8 @@ chat_mode = "normal" # 聊天模式 —— 普通模式：normal，专注模式
 # chat_mode = "focus"
 # chat_mode = "auto"
 
+auto_focus_threshold = 1 # 自动切换到专注聊天的阈值，越低越容易进入专注聊天
+exit_focus_threshold = 1 # 自动退出专注聊天的阈值，越低越容易退出专注聊天
 # 普通模式下，麦麦会针对感兴趣的消息进行回复，token消耗量较低
 # 专注模式下，麦麦会进行主动的观察和回复，并给出回复，token消耗量较高
 # 自动模式下，麦麦会根据消息内容自动切换到专注模式或普通模式
@@ -79,9 +81,6 @@ at_bot_inevitable_reply = false # @bot 必然回复
 talk_frequency_down_groups = []  #降低回复频率的群号码
 
 [focus_chat] #专注聊天
-auto_focus_threshold = 1 # 自动切换到专注聊天的阈值，越低越容易进入专注聊天
-exit_focus_threshold = 1 # 自动退出专注聊天的阈值，越低越容易退出专注聊天
-
 think_interval = 3 # 思考间隔 单位秒，可以有效减少消耗
 
 observation_context_size = 15 # 观察到的最长上下文大小,建议15，太短太长都会导致脑袋尖尖