better：重整配置，分离表达，聊天模式区分

重整配置文件路径，添加更多配置选项
分离了人设表达方式和学习到的表达方式
将聊天模式区分为normal focus和auto

src/chat/focus_chat/info_processors/action_processor.py

@@ -1,14 +1,10 @@
 from typing import List, Optional, Any
-from src.chat.focus_chat.info.obs_info import ObsInfo
 from src.chat.heart_flow.observation.observation import Observation
 from src.chat.focus_chat.info.info_base import InfoBase
 from src.chat.focus_chat.info.action_info import ActionInfo
 from .base_processor import BaseProcessor
 from src.common.logger_manager import get_logger
-from src.chat.heart_flow.observation.chatting_observation import ChattingObservation
 from src.chat.heart_flow.observation.hfcloop_observation import HFCloopObservation
-from src.chat.focus_chat.info.cycle_info import CycleInfo
-from datetime import datetime
 from typing import Dict
 from src.chat.models.utils_model import LLMRequest
 from src.config.config import global_config
@@ -55,10 +51,7 @@ class ActionProcessor(BaseProcessor):
         # 处理Observation对象
         if observations:
             for obs in observations:
-
                 if isinstance(obs, HFCloopObservation):
-
-
                     # 创建动作信息
                     action_info = ActionInfo()
                     action_changes = await self.analyze_loop_actions(obs)
@@ -75,7 +68,6 @@ class ActionProcessor(BaseProcessor):
 
         return processed_infos
 
-
     async def analyze_loop_actions(self, obs: HFCloopObservation) -> Dict[str, List[str]]:
         """分析最近的循环内容并决定动作的增减
 
@@ -87,29 +79,29 @@ class ActionProcessor(BaseProcessor):
                 }
         """
         result = {"add": [], "remove": []}
-        
+
         # 获取最近10次循环
         recent_cycles = obs.history_loop[-10:] if len(obs.history_loop) > 10 else obs.history_loop
         if not recent_cycles:
             return result
-            
+
         # 统计no_reply的数量
         no_reply_count = 0
         reply_sequence = []  # 记录最近的动作序列
-        
+
         for cycle in recent_cycles:
             action_type = cycle.loop_plan_info["action_result"]["action_type"]
             if action_type == "no_reply":
                 no_reply_count += 1
             reply_sequence.append(action_type == "reply")
-            
+
         # 检查no_reply比例
         if len(recent_cycles) >= 5 and (no_reply_count / len(recent_cycles)) >= 0.8:
             result["add"].append("exit_focus_chat")
-            
+
         # 获取最近三次的reply状态
         last_three = reply_sequence[-3:] if len(reply_sequence) >= 3 else reply_sequence
-        
+
         # 根据最近的reply情况决定是否移除reply动作
         if len(last_three) >= 3 and all(last_three):
             # 如果最近三次都是reply，直接移除
@@ -122,5 +114,5 @@ class ActionProcessor(BaseProcessor):
             # 如果最近一次是reply，20%概率移除
             if random.random() < 0.2:
                 result["remove"].append("reply")
-                
+
         return result

src/chat/focus_chat/info_processors/mind_processor.py

@@ -5,7 +5,7 @@ from src.config.config import global_config
 import time
 import traceback
 from src.common.logger_manager import get_logger
-from src.individuality.individuality import Individuality
+from src.individuality.individuality import individuality
 from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
 from src.chat.utils.json_utils import safe_json_dumps
 from src.chat.message_receive.chat_stream import chat_manager
@@ -194,7 +194,6 @@ class MindProcessor(BaseProcessor):
 
         # ---------- 3. 准备个性化数据 ----------
         # 获取个性化信息
-        individuality = Individuality.get_instance()
 
         relation_prompt = ""
         for person in person_list:

src/chat/focus_chat/info_processors/self_processor.py

@@ -5,7 +5,7 @@ from src.config.config import global_config
 import time
 import traceback
 from src.common.logger_manager import get_logger
-from src.individuality.individuality import Individuality
+from src.individuality.individuality import individuality
 from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
 from src.chat.message_receive.chat_stream import chat_manager
 from src.chat.person_info.relationship_manager import relationship_manager
@@ -21,8 +21,9 @@ logger = get_logger("processor")
 
 def init_prompt():
     indentify_prompt = """
-你的名字是{bot_name},你是一个AI，但是你伪装成了一个人类，你的人格是，{prompt_personality}。
-你的头像形象是一只橙色的鱼，头上有绿色的树叶。
+{name_block}
+你是一个AI，但是你伪装成了一个人类，你的人格是，{prompt_personality}。
+{indentify_block}
 
 {relation_prompt}
 {memory_str}
@@ -125,16 +126,22 @@ class SelfProcessor(BaseProcessor):
                 # hfcloop_observe_info = observation.get_observe_info()
                 pass
 
-        individuality = Individuality.get_instance()
-        personality_block = individuality.get_prompt(x_person=2, level=2)
+        nickname_str = ""
+        for nicknames in global_config.bot.alias_names:
+            nickname_str += f"{nicknames},"
+        name_block = f"你的名字是{global_config.bot.nickname},你的昵称有{nickname_str}，有人也会用这些昵称称呼你。"
+
+        personality_block = individuality.get_personality_prompt(x_person=2, level=2)
+        identity_block = individuality.get_identity_prompt(x_person=2, level=2)
 
         relation_prompt = ""
         for person in person_list:
             relation_prompt += await relationship_manager.build_relationship_info(person, is_id=True)
 
         prompt = (await global_prompt_manager.get_prompt_async("indentify_prompt")).format(
-            bot_name=individuality.name,
+            name_block=name_block,
             prompt_personality=personality_block,
+            indentify_block=identity_block,
             memory_str=memory_str,
             relation_prompt=relation_prompt,
             time_now=time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()),

src/chat/focus_chat/info_processors/tool_processor.py

@@ -3,7 +3,7 @@ from src.chat.models.utils_model import LLMRequest
 from src.config.config import global_config
 import time
 from src.common.logger_manager import get_logger
-from src.individuality.individuality import Individuality
+from src.individuality.individuality import individuality
 from src.chat.utils.prompt_builder import Prompt, global_prompt_manager
 from src.tools.tool_use import ToolUser
 from src.chat.utils.json_utils import process_llm_tool_calls
@@ -133,7 +133,7 @@ class ToolProcessor(BaseProcessor):
             relation_prompt += await relationship_manager.build_relationship_info(person, is_id=True)
 
         # 获取个性信息
-        individuality = Individuality.get_instance()
+
         # prompt_personality = individuality.get_prompt(x_person=2, level=2)
 
         # 获取时间信息