feat：新增用户侧写功能

src/person_info/relationship_manager.py

@@ -1,26 +1,29 @@
 from src.common.logger_manager import get_logger
 from src.chat.message_receive.chat_stream import ChatStream
 import math
-from bson.decimal128 import Decimal128
 from src.person_info.person_info import person_info_manager
 import time
 import random
-from maim_message import UserInfo
-
+from src.llm_models.utils_model import LLMRequest
+from src.config.config import global_config
+from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat_users
+from src.chat.utils.chat_message_builder import build_readable_messages
 from src.manager.mood_manager import mood_manager
 
-# import re
-# import traceback
-
 
 logger = get_logger("relation")
 
-
 class RelationshipManager:
     def __init__(self):
         self.positive_feedback_value = 0  # 正反馈系统
         self.gain_coefficient = [1.0, 1.0, 1.1, 1.2, 1.4, 1.7, 1.9, 2.0]
         self._mood_manager = None
+        
+        self.relationship_llm = LLMRequest(
+            model=global_config.model.normal_chat_1,
+            max_tokens=1000,
+            request_type="relationship",  # 用于动作规划
+        )
 
     @property
     def mood_manager(self):
@@ -112,91 +115,6 @@ class RelationshipManager:
             person_id=person_id, user_nickname=user_nickname, user_cardname=user_cardname, user_avatar=user_avatar
         )
 
-    async def calculate_update_relationship_value(self, user_info: UserInfo, platform: str, label: str, stance: str):
-        """计算并变更关系值
-        新的关系值变更计算方式：
-            将关系值限定在-1000到1000
-            对于关系值的变更，期望：
-                1.向两端逼近时会逐渐减缓
-                2.关系越差，改善越难，关系越好，恶化越容易
-                3.人维护关系的精力往往有限，所以当高关系值用户越多，对于中高关系值用户增长越慢
-                4.连续正面或负面情感会正反馈
-
-        返回：
-            用户昵称，变更值，变更后关系等级
-
-        """
-        stancedict = {
-            "支持": 0,
-            "中立": 1,
-            "反对": 2,
-        }
-
-        valuedict = {
-            "开心": 1.5,
-            "愤怒": -2.0,
-            "悲伤": -0.5,
-            "惊讶": 0.6,
-            "害羞": 2.0,
-            "平静": 0.3,
-            "恐惧": -1.5,
-            "厌恶": -1.0,
-            "困惑": 0.5,
-        }
-
-        person_id = person_info_manager.get_person_id(platform, user_info.user_id)
-        data = {
-            "platform": platform,
-            "user_id": user_info.user_id,
-            "nickname": user_info.user_nickname,
-            "konw_time": int(time.time()),
-        }
-        old_value = await person_info_manager.get_value(person_id, "relationship_value")
-        old_value = self.ensure_float(old_value, person_id)
-
-        if old_value > 1000:
-            old_value = 1000
-        elif old_value < -1000:
-            old_value = -1000
-
-        value = valuedict[label]
-        if old_value >= 0:
-            if valuedict[label] >= 0 and stancedict[stance] != 2:
-                value = value * math.cos(math.pi * old_value / 2000)
-                if old_value > 500:
-                    rdict = await person_info_manager.get_specific_value_list("relationship_value", lambda x: x > 700)
-                    high_value_count = len(rdict)
-                    if old_value > 700:
-                        value *= 3 / (high_value_count + 2)  # 排除自己
-                    else:
-                        value *= 3 / (high_value_count + 3)
-            elif valuedict[label] < 0 and stancedict[stance] != 0:
-                value = value * math.exp(old_value / 2000)
-            else:
-                value = 0
-        elif old_value < 0:
-            if valuedict[label] >= 0 and stancedict[stance] != 2:
-                value = value * math.exp(old_value / 2000)
-            elif valuedict[label] < 0 and stancedict[stance] != 0:
-                value = value * math.cos(math.pi * old_value / 2000)
-            else:
-                value = 0
-
-        self.positive_feedback_sys(label, stance)
-        value = self.mood_feedback(value)
-
-        level_num = self.calculate_level_num(old_value + value)
-        relationship_level = ["厌恶", "冷漠", "一般", "友好", "喜欢", "暧昧"]
-        logger.info(
-            f"用户: {user_info.user_nickname}"
-            f"当前关系: {relationship_level[level_num]}, "
-            f"关系值: {old_value:.2f}, "
-            f"当前立场情感: {stance}-{label}, "
-            f"变更: {value:+.5f}"
-        )
-
-        await person_info_manager.update_one_field(person_id, "relationship_value", old_value + value, data)
-
     async def calculate_update_relationship_value_with_reason(
         self, chat_stream: ChatStream, label: str, stance: str, reason: str
     ) -> tuple:
@@ -337,6 +255,14 @@ class RelationshipManager:
             relation_prompt = f"{relation_value_prompt}，ta在{platform}上的昵称是{nickname_str}。\n"
         else:
             relation_prompt = ""
+            
+        person_name_reason = await person_info_manager.get_value(person_id, "person_name_reason")
+        if person_name_reason:
+            relation_prompt += f"ta的昵称{person_name}的由来是：{person_name_reason}。\n"
+            
+        person_impression = await person_info_manager.get_value(person_id, "person_impression")
+        if person_impression:
+            relation_prompt += f"ta的印象是：{person_impression}。\n"
 
         return relation_prompt
 
@@ -358,17 +284,95 @@ class RelationshipManager:
         else:
             level_num = 5 if relationship_value > 1000 else 0
         return level_num
+    
+    
+    async def update_person_impression(self, person_id, chat_id, reason, timestamp):
+        """更新用户印象
+        
+        Args:
+            person_id: 用户ID
+            chat_id: 聊天ID
+            reason: 更新原因
+            timestamp: 时间戳
+        """
+        # 获取现有印象和用户信息
+        person_name = await person_info_manager.get_value(person_id, "person_name")
+        nickname = await person_info_manager.get_value(person_id, "nickname")
+        old_impression = await person_info_manager.get_value(person_id, "person_impression")
+        user_id = await person_info_manager.get_value(person_id, "user_id")
+        
+        logger.debug(f"更新印象的person_id: {person_id}, chat_id: {chat_id}, reason: {reason}, timestamp: {timestamp}, user_id: {user_id}")
 
-    @staticmethod
-    def ensure_float(value, person_id):
-        """确保返回浮点数，转换失败返回0.0"""
-        if isinstance(value, float):
-            return value
-        try:
-            return float(value.to_decimal() if isinstance(value, Decimal128) else value)
-        except (ValueError, TypeError, AttributeError):
-            logger.warning(f"[关系管理] {person_id}值转换失败（原始值：{value}），已重置为0")
-            return 0.0
+        # 获取时间戳前后的消息
+        messages_before = get_raw_msg_by_timestamp_with_chat_users(
+            chat_id=chat_id,
+            timestamp_start=timestamp - 3600,  # 前1小时
+            timestamp_end=timestamp,
+            person_ids=[user_id],
+            limit=30,
+            limit_mode="latest"
+        )
+        
+        messages_after = get_raw_msg_by_timestamp_with_chat_users(
+            chat_id=chat_id,
+            timestamp_start=timestamp,
+            timestamp_end=timestamp + 3600,  # 后1小时
+            person_ids=[user_id],
+            limit=30,
+            limit_mode="earliest"
+        )
+        
+        # 合并消息并按时间排序
+        user_messages = messages_before + messages_after
+        user_messages.sort(key=lambda x: x["time"])
+        
+        # print(f"user_messages: {user_messages}")
+        
+        # 构建可读消息
+        
+        readable_messages = await build_readable_messages(
+            messages=user_messages,
+            replace_bot_name=True,
+            timestamp_mode="relative",
+            truncate=False
+        )
+        
+        # 使用LLM总结印象
+        prompt = f"""基于以下信息，总结对{person_name}(昵称:{nickname})的印象：
+原因：{reason}
+历史印象：{old_impression if old_impression else '无'}
+最近发言：
+{readable_messages}
+
+请用简洁的语言总结对这个人的印象，不超过200字。"""
+        
+        new_impression, _ = await self.relationship_llm.generate_response_async(prompt=prompt)
+        
+        
+        logger.debug(f"新印象prompt：{prompt}")
+        logger.info(f"新印象：{new_impression}")
+        
+        
+        # 合并新旧印象
+        if old_impression:
+            merge_prompt = f"""请将以下两段印象合并，形成一段连贯的描述：
+旧印象：{old_impression}
+新印象：{new_impression}
+
+请用简洁的语言合并这两段印象，不超过200字。"""
+            final_impression, _ = await self.relationship_llm.generate_response_async(prompt=merge_prompt)
+            
+            logger.debug(f"合并印象prompt：{merge_prompt}")
+            logger.info(f"合并印象：{final_impression}")
+            
+        else:
+            final_impression = new_impression
+            
+            
+        # 更新到数据库
+        await person_info_manager.update_one_field(person_id, "person_impression", final_impression)
+        
+        return final_impression
 
 
 relationship_manager = RelationshipManager()