better：优化关系prompt，回退utils的修改

src/llm_models/utils_model.py

@@ -124,20 +124,14 @@ class LLMRequest:
         self.model_name: str = model["name"]
         self.params = kwargs
 
-        self.enable_thinking = model.get("enable_thinking", None)
+        self.enable_thinking = model.get("enable_thinking", False)
         self.temp = model.get("temp", 0.7)
-        self.thinking_budget = model.get("thinking_budget", None)
+        self.thinking_budget = model.get("thinking_budget", 4096)
         self.stream = model.get("stream", False)
         self.pri_in = model.get("pri_in", 0)
         self.pri_out = model.get("pri_out", 0)
         self.max_tokens = model.get("max_tokens", global_config.model.model_max_output_length)
         # print(f"max_tokens: {self.max_tokens}")
-        custom_params_str = model.get("custom_params", "{}")
-        try:
-            self.custom_params = json.loads(custom_params_str)
-        except json.JSONDecodeError:
-            logger.error(f"Invalid JSON in custom_params for model '{self.model_name}': {custom_params_str}")
-            self.custom_params = {}
 
         # 获取数据库实例
         self._init_database()
@@ -255,6 +249,28 @@ class LLMRequest:
         elif payload is None:
             payload = await self._build_payload(prompt)
 
+        if stream_mode:
+            payload["stream"] = stream_mode
+
+        if self.temp != 0.7:
+            payload["temperature"] = self.temp
+
+        # 添加enable_thinking参数（如果不是默认值False）
+        if not self.enable_thinking:
+            payload["enable_thinking"] = False
+
+        if self.thinking_budget != 4096:
+            payload["thinking_budget"] = self.thinking_budget
+
+        if self.max_tokens:
+            payload["max_tokens"] = self.max_tokens
+
+        # if "max_tokens" not in payload and "max_completion_tokens" not in payload:
+        # payload["max_tokens"] = global_config.model.model_max_output_length
+        # 如果 payload 中依然存在 max_tokens 且需要转换，在这里进行再次检查
+        if self.model_name.lower() in self.MODELS_NEEDING_TRANSFORMATION and "max_tokens" in payload:
+            payload["max_completion_tokens"] = payload.pop("max_tokens")
+
         return {
             "policy": policy,
             "payload": payload,
@@ -654,16 +670,18 @@ class LLMRequest:
         if self.temp != 0.7:
             payload["temperature"] = self.temp
 
-        # 仅当配置文件中存在参数时，添加对应参数
+        # 添加enable_thinking参数（如果不是默认值False）
-        if self.enable_thinking is not None:
+        if not self.enable_thinking:
-            payload["enable_thinking"] = self.enable_thinking
+            payload["enable_thinking"] = False
 
-        if self.thinking_budget is not None:
+        if self.thinking_budget != 4096:
             payload["thinking_budget"] = self.thinking_budget
 
         if self.max_tokens:
             payload["max_tokens"] = self.max_tokens
 
+        # if "max_tokens" not in payload and "max_completion_tokens" not in payload:
+        # payload["max_tokens"] = global_config.model.model_max_output_length
         # 如果 payload 中依然存在 max_tokens 且需要转换，在这里进行再次检查
         if self.model_name.lower() in self.MODELS_NEEDING_TRANSFORMATION and "max_tokens" in payload:
             payload["max_completion_tokens"] = payload.pop("max_tokens")

src/person_info/relationship_fetcher.py

@@ -9,7 +9,7 @@ from typing import List, Dict
 from json_repair import repair_json
 from src.chat.message_receive.chat_stream import get_chat_manager
 import json
-
+import random
 
 logger = get_logger("relationship_fetcher")
 
@@ -101,22 +101,69 @@ class RelationshipFetcher:
         person_name = await person_info_manager.get_value(person_id, "person_name")
         short_impression = await person_info_manager.get_value(person_id, "short_impression")
         
+        nickname_str = await person_info_manager.get_value(person_id, "nickname")
+        platform = await person_info_manager.get_value(person_id, "platform")
+        
+        if person_name == nickname_str and not short_impression:
+            return ""
+        
+        current_points = await person_info_manager.get_value(person_id, "points") or []
+
+        if isinstance(current_points, str):
+            try:
+                current_points = json.loads(current_points)
+            except json.JSONDecodeError:
+                logger.error(f"解析points JSON失败: {current_points}")
+                current_points = []
+        elif not isinstance(current_points, list):
+            current_points = []
+
+        # 按时间排序forgotten_points
+        current_points.sort(key=lambda x: x[2])
+        # 按权重加权随机抽取3个points，point[1]的值在1-10之间，权重越高被抽到概率越大
+        if len(current_points) > 3:
+            # point[1] 取值范围1-10，直接作为权重
+            weights = [max(1, min(10, int(point[1]))) for point in current_points]
+            points = random.choices(current_points, weights=weights, k=3)
+        else:
+            points = current_points
+
+        # 构建points文本
+        points_text = "\n".join([f"{point[2]}：{point[0]}" for point in points])
+
         info_type = await self._build_fetch_query(person_id, target_message, chat_history)
         if info_type:
             await self._extract_single_info(person_id, info_type, person_name)
 
         relation_info = self._organize_known_info()
+        
+        nickname_str = ""
+        if person_name != nickname_str:
+            nickname_str = f"(ta在{platform}上的昵称是{nickname_str})"
+        
         if short_impression and relation_info:
-            relation_info = f"你对{person_name}的印象是：{short_impression}。具体来说：{relation_info}"
+            if points_text:
+                relation_info = f"你对{person_name}的印象是{nickname_str}：{short_impression}。具体来说：{relation_info}。你还记得ta最近做的事：{points_text}"
+            else:
+                relation_info = f"你对{person_name}的印象是{nickname_str}：{short_impression}。具体来说：{relation_info}"
         elif short_impression:
-            relation_info = f"你对{person_name}的印象是：{short_impression}"
+            if points_text:
+                relation_info = f"你对{person_name}的印象是{nickname_str}：{short_impression}。你还记得ta最近做的事：{points_text}"
+            else:
+                relation_info = f"你对{person_name}的印象是{nickname_str}：{short_impression}"
         elif relation_info:
-            relation_info = f"你对{person_name}的了解：{relation_info}"
+            if points_text:
+                relation_info = f"你对{person_name}的了解{nickname_str}：{relation_info}。你还记得ta最近做的事：{points_text}"
+            else:
+                relation_info = f"你对{person_name}的了解{nickname_str}：{relation_info}"
+        elif points_text:
+            relation_info = f"你记得{person_name}{nickname_str}最近做的事：{points_text}"
         else:
             relation_info = ""
 
         return relation_info
 
+
     async def _build_fetch_query(self, person_id, target_message, chat_history):
         nickname_str = ",".join(global_config.bot.alias_names)
         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。"

src/person_info/relationship_manager.py

@@ -126,6 +126,7 @@ class RelationshipManager:
         short_impression = await person_info_manager.get_value(person_id, "short_impression")
 
         current_points = await person_info_manager.get_value(person_id, "points") or []
+        print(f"current_points: {current_points}")
         if isinstance(current_points, str):
             try:
                 current_points = json.loads(current_points)