feat：可选择是否压缩人设

src/chat/express/expression_selector.py

@@ -240,7 +240,7 @@ class ExpressionSelector:
                     valid_expressions.append(expression)
 
                     # 对选中的表达方式count数+0.1
-                    self.update_expression_count(chat_id, expression, 0.1)
+                    self.update_expression_count(chat_id, expression, 0.0001)
 
             # logger.info(f"LLM从{len(all_expressions)}个情境中选择了{len(valid_expressions)}个")
             return valid_expressions

src/chat/focus_chat/replyer/default_generator.py

@@ -19,6 +19,8 @@ from src.chat.utils.chat_message_builder import build_readable_messages, get_raw
 from src.chat.express.exprssion_learner import get_expression_learner
 import time
 import random
+import ast
+from src.person_info.person_info import get_person_info_manager
 from datetime import datetime
 import re
 
@@ -277,6 +279,8 @@ class DefaultReplyer:
         reply_data=None,
     ) -> str:
         chat_stream = self.chat_stream
+        person_info_manager = get_person_info_manager()
+        bot_person_id = person_info_manager.get_person_id("system", "bot_id")
 
         is_group_chat = bool(chat_stream.group_info)
 
@@ -389,8 +393,26 @@ class DefaultReplyer:
             bot_nickname = f",也有人叫你{','.join(global_config.bot.alias_names)}"
         else:
             bot_nickname = ""
-        bot_core_personality = global_config.personality.personality_core
+        short_impression = await person_info_manager.get_value(bot_person_id, "short_impression")
-        indentify_block = f"你的名字是{bot_name}{bot_nickname}，你{bot_core_personality}："
+                # 解析字符串形式的Python列表
+        try:
+            if isinstance(short_impression, str) and short_impression.strip():
+                short_impression = ast.literal_eval(short_impression)
+            elif not short_impression:
+                logger.warning("short_impression为空，使用默认值")
+                short_impression = ["友好活泼", "人类"]
+        except (ValueError, SyntaxError) as e:
+            logger.error(f"解析short_impression失败: {e}, 原始值: {short_impression}")
+            short_impression = ["友好活泼", "人类"]
+        
+        # 确保short_impression是列表格式且有足够的元素
+        if not isinstance(short_impression, list) or len(short_impression) < 2:
+            logger.warning(f"short_impression格式不正确: {short_impression}, 使用默认值")
+            short_impression = ["友好活泼", "人类"]
+        personality = short_impression[0]
+        identity = short_impression[1]
+        prompt_personality = personality + "，" + identity
+        indentify_block = f"你的名字是{bot_name}{bot_nickname}，你{prompt_personality}："
 
         if sender:
             reply_target_block = f"现在{sender}说的:{target}。引起了你的注意，你想要在群里发言或者回复这条消息。"

src/chat/normal_chat/normal_prompt.py

@@ -11,6 +11,8 @@ import random
 from src.person_info.person_info import get_person_info_manager
 from src.chat.express.expression_selector import expression_selector
 import re
+import json
+import ast
 
 from src.person_info.relationship_manager import get_relationship_manager
 
@@ -91,13 +93,30 @@ class PromptBuilder:
         enable_planner: bool = False,
         available_actions=None,
     ) -> str:
-        core_personality = global_config.personality.personality_core
         person_info_manager = get_person_info_manager()
         bot_person_id = person_info_manager.get_person_id("system", "bot_id")
+        
         short_impression = await person_info_manager.get_value(bot_person_id, "short_impression")
-        prompt_personality = core_personality
+        
-        if short_impression:
+        # 解析字符串形式的Python列表
-            prompt_personality += short_impression
+        try:
+            if isinstance(short_impression, str) and short_impression.strip():
+                short_impression = ast.literal_eval(short_impression)
+            elif not short_impression:
+                logger.warning("short_impression为空，使用默认值")
+                short_impression = ["友好活泼", "人类"]
+        except (ValueError, SyntaxError) as e:
+            logger.error(f"解析short_impression失败: {e}, 原始值: {short_impression}")
+            short_impression = ["友好活泼", "人类"]
+        
+        # 确保short_impression是列表格式且有足够的元素
+        if not isinstance(short_impression, list) or len(short_impression) < 2:
+            logger.warning(f"short_impression格式不正确: {short_impression}, 使用默认值")
+            short_impression = ["友好活泼", "人类"]
+            
+        personality = short_impression[0]
+        identity = short_impression[1]
+        prompt_personality = personality + "，" + identity
 
         is_group_chat = bool(chat_stream.group_info)
 

src/config/official_configs.py

@@ -37,6 +37,9 @@ class PersonalityConfig(ConfigBase):
     personality_sides: list[str] = field(default_factory=lambda: [])
     """人格侧写"""
 
+    compress_personality: bool = True
+    """是否压缩人格，压缩后会精简人格信息，节省token消耗并提高回复性能，但是会丢失一些信息，如果人设不长，可以关闭"""
+
 
 @dataclass
 class IdentityConfig(ConfigBase):
@@ -45,6 +48,9 @@ class IdentityConfig(ConfigBase):
     identity_detail: list[str] = field(default_factory=lambda: [])
     """身份特征"""
 
+    compress_indentity: bool = True
+    """是否压缩身份，压缩后会精简身份信息，节省token消耗并提高回复性能，但是会丢失一些信息，如果不长，可以关闭"""
+
 
 @dataclass
 class RelationshipConfig(ConfigBase):

src/individuality/individuality.py

@@ -58,7 +58,7 @@ class Individuality:
         self.name = bot_nickname
 
         # 检查配置变化，如果变化则清空
-        await self._check_config_and_clear_if_changed(
+        personality_changed, identity_changed = await self._check_config_and_clear_if_changed(
             bot_nickname, personality_core, personality_sides, identity_detail
         )
 
@@ -96,10 +96,59 @@ class Individuality:
             await person_info_manager.update_one_field(
                 self.bot_person_id, "impression", impression_text, data=update_data
             )
-            logger.info("已将完整人设更新到bot的impression中")
+            logger.debug("已将完整人设更新到bot的impression中")
 
-        # 创建压缩版本的short_impression
+        # 根据变化情况决定是否重新创建
-        asyncio.create_task(self._create_compressed_impression(personality_core, personality_sides, identity_detail))
+        personality_result = None
+        identity_result = None
+        
+        if personality_changed:
+            logger.info("检测到人格配置变化，重新生成压缩版本")
+            personality_result = await self._create_personality(personality_core, personality_sides)
+        else:
+            logger.info("人格配置未变化，使用缓存版本")
+            # 从缓存中获取已有的personality结果
+            existing_short_impression = await person_info_manager.get_value(self.bot_person_id, "short_impression")
+            if existing_short_impression:
+                try:
+                    existing_data = json.loads(existing_short_impression) if isinstance(existing_short_impression, str) else existing_short_impression
+                    if isinstance(existing_data, list) and len(existing_data) >= 1:
+                        personality_result = existing_data[0]
+                except (json.JSONDecodeError, TypeError, IndexError):
+                    logger.warning("无法解析现有的short_impression，将重新生成人格部分")
+                    personality_result = await self._create_personality(personality_core, personality_sides)
+            else:
+                logger.info("未找到现有的人格缓存，重新生成")
+                personality_result = await self._create_personality(personality_core, personality_sides)
+        
+        if identity_changed:
+            logger.info("检测到身份配置变化，重新生成压缩版本")
+            identity_result = await self._create_identity(identity_detail)
+        else:
+            logger.info("身份配置未变化，使用缓存版本")
+            # 从缓存中获取已有的identity结果
+            existing_short_impression = await person_info_manager.get_value(self.bot_person_id, "short_impression")
+            if existing_short_impression:
+                try:
+                    existing_data = json.loads(existing_short_impression) if isinstance(existing_short_impression, str) else existing_short_impression
+                    if isinstance(existing_data, list) and len(existing_data) >= 2:
+                        identity_result = existing_data[1]
+                except (json.JSONDecodeError, TypeError, IndexError):
+                    logger.warning("无法解析现有的short_impression，将重新生成身份部分")
+                    identity_result = await self._create_identity(identity_detail)
+            else:
+                logger.info("未找到现有的身份缓存，重新生成")
+                identity_result = await self._create_identity(identity_detail)
+        
+        result = [personality_result, identity_result]
+        
+        # 更新short_impression字段
+        if personality_result and identity_result:
+            person_info_manager = get_person_info_manager()
+            await person_info_manager.update_one_field(self.bot_person_id, "short_impression", result)
+            logger.info("已将人设构建")
+        else:
+            logger.error("人设构建失败")
             
         asyncio.create_task(self.express_style.extract_and_store_personality_expressions())
 
@@ -271,31 +320,61 @@ class Individuality:
 
     def _get_config_hash(
         self, bot_nickname: str, personality_core: str, personality_sides: list, identity_detail: list
-    ) -> str:
+    ) -> tuple[str, str]:
-        """获取当前personality和identity配置的哈希值"""
+        """获取personality和identity配置的哈希值
-        config_data = {
+        
+        Returns:
+            tuple: (personality_hash, identity_hash)
+        """
+        # 人格配置哈希
+        personality_config = {
             "nickname": bot_nickname,
             "personality_core": personality_core,
             "personality_sides": sorted(personality_sides),
-            "identity_detail": sorted(identity_detail),
+            "compress_personality": global_config.personality.compress_personality,
         }
-        config_str = json.dumps(config_data, sort_keys=True)
+        personality_str = json.dumps(personality_config, sort_keys=True)
-        return hashlib.md5(config_str.encode("utf-8")).hexdigest()
+        personality_hash = hashlib.md5(personality_str.encode("utf-8")).hexdigest()
+        
+        # 身份配置哈希
+        identity_config = {
+            "identity_detail": sorted(identity_detail),
+            "compress_identity": global_config.identity.compress_indentity,
+        }
+        identity_str = json.dumps(identity_config, sort_keys=True)
+        identity_hash = hashlib.md5(identity_str.encode("utf-8")).hexdigest()
+        
+        return personality_hash, identity_hash
 
     async def _check_config_and_clear_if_changed(
         self, bot_nickname: str, personality_core: str, personality_sides: list, identity_detail: list
-    ):
+    ) -> tuple[bool, bool]:
-        """检查配置是否发生变化，如果变化则清空info_list"""
+        """检查配置是否发生变化，如果变化则清空相应缓存
+        
+        Returns:
+            tuple: (personality_changed, identity_changed)
+        """
         person_info_manager = get_person_info_manager()
-        current_hash = self._get_config_hash(bot_nickname, personality_core, personality_sides, identity_detail)
+        current_personality_hash, current_identity_hash = self._get_config_hash(
+            bot_nickname, personality_core, personality_sides, identity_detail
+        )
 
         meta_info = self._load_meta_info()
-        stored_hash = meta_info.get("config_hash")
+        stored_personality_hash = meta_info.get("personality_hash")
+        stored_identity_hash = meta_info.get("identity_hash")
 
-        if current_hash != stored_hash:
+        personality_changed = current_personality_hash != stored_personality_hash
-            logger.info("检测到人格配置发生变化，将清空原有的关键词缓存。")
+        identity_changed = current_identity_hash != stored_identity_hash
 
-            # 清空数据库中的info_list
+        if personality_changed:
+            logger.info("检测到人格配置发生变化")
+
+        if identity_changed:
+            logger.info("检测到身份配置发生变化")
+
+        # 如果任何一个发生变化，都需要清空info_list（因为这影响整体人设）
+        if personality_changed or identity_changed:
+            logger.info("将清空原有的关键词缓存")
             update_data = {
                 "platform": "system",
                 "user_id": "bot_id",
@@ -304,10 +383,15 @@ class Individuality:
             }
             await person_info_manager.update_one_field(self.bot_person_id, "info_list", [], data=update_data)
 
-            # 更新元信息文件，重置计数器
+        # 更新元信息文件
-            new_meta_info = {"config_hash": current_hash}
+        new_meta_info = {
+            "personality_hash": current_personality_hash,
+            "identity_hash": current_identity_hash,
+        }
         self._save_meta_info(new_meta_info)
 
+        return personality_changed, identity_changed
+
     def _load_meta_info(self) -> dict:
         """从JSON文件中加载元信息"""
         if os.path.exists(self.meta_info_file_path):
@@ -368,8 +452,8 @@ class Individuality:
                 logger.error(f"解析info_list失败: {info_list_json}")
         return keywords
 
-    async def _create_compressed_impression(
+    async def _create_personality(
-        self, personality_core: str, personality_sides: list, identity_detail: list
+        self, personality_core: str, personality_sides: list
     ) -> str:
         """使用LLM创建压缩版本的impression
 
@@ -381,30 +465,23 @@ class Individuality:
         Returns:
             str: 压缩后的impression文本
         """
+        logger.info("正在构建人格.........")
+        
+        
         # 核心人格保持不变
-        compressed_parts = []
+        personality_parts = []
         if personality_core:
-            compressed_parts.append(f"{personality_core}")
+            personality_parts.append(f"{personality_core}")
 
         # 准备需要压缩的内容
-        content_to_compress = []
+        if global_config.personality.compress_personality:
+            personality_to_compress = []
             if personality_sides:
-            content_to_compress.append(f"人格特质: {'、'.join(personality_sides)}")
+                personality_to_compress.append(f"人格特质: {'、'.join(personality_sides)}")
-        if identity_detail:
-            content_to_compress.append(f"身份背景: {'、'.join(identity_detail)}")
                 
-        if not content_to_compress:
-            # 如果没有需要压缩的内容，直接返回核心人格
-            result = "。".join(compressed_parts)
-            return result + "。" if result else ""
                 
-        # 使用LLM压缩其他内容
+                prompt = f"""请将以下人格信息进行简洁压缩，保留主要内容，用简练的中文表达：
-        try:
+{personality_to_compress}
-            compress_content = "、".join(content_to_compress)
-
-            prompt = f"""请将以下人设信息进行简洁压缩，保留主要内容，用简练的中文表达：
-
-{compress_content}
 
 要求：
 1. 保持原意不变，尽量使用原文
@@ -416,20 +493,55 @@ class Individuality:
                 )
                 
                 if response.strip():
-                compressed_parts.append(response.strip())
+                    personality_parts.append(response.strip())
                     logger.info(f"精简人格侧面: {response.strip()}")
                 else:
                     logger.error(f"使用LLM压缩人设时出错: {response}")
-        except Exception as e:
+                if personality_parts:
-            logger.error(f"使用LLM压缩人设时出错: {e}")
+                    personality_result = "。".join(personality_parts)
+                else:
+                    personality_result = personality_core
+        else:
+            personality_result = personality_core
+            if personality_sides:
+                personality_result += "，".join(personality_sides)
             
-        result = "。".join(compressed_parts)
 
-        # 更新short_impression字段
+        return personality_result
-        if result:
+
-            person_info_manager = get_person_info_manager()
+    async def _create_identity(self, identity_detail: list) -> str:
-            await person_info_manager.update_one_field(self.bot_person_id, "short_impression", result)
+        """使用LLM创建压缩版本的impression
-            logger.info("已将压缩人设更新到bot的short_impression中")
+        """
+        logger.info("正在构建身份.........")
+        
+        if global_config.identity.compress_indentity:
+            identity_to_compress = []
+            if identity_detail:
+                identity_to_compress.append(f"身份背景: {'、'.join(identity_detail)}")
+
+            prompt = f"""请将以下身份信息进行简洁压缩，保留主要内容，用简练的中文表达：
+{identity_to_compress}
+
+要求：
+1. 保持原意不变，尽量使用原文
+2. 尽量简洁，不超过30字
+3. 直接输出压缩后的内容，不要解释"""
+
+            response, (_, _) = await self.model.generate_response_async(
+                prompt=prompt,
+            )
+
+            if response.strip():
+                identity_result = response.strip()
+                logger.info(f"精简身份: {identity_result}")
+            else:
+                logger.error(f"使用LLM压缩身份时出错: {response}")
+        else:
+            identity_result = "。".join(identity_detail)
+            
+        
+        return identity_result
+
 
 
 individuality = None

template/bot_config_template.toml

@@ -1,5 +1,5 @@
 [inner]
-version = "2.27.0"
+version = "2.28.0"
 
 #----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，请在修改后将version的值进行变更
@@ -18,25 +18,29 @@ nickname = "麦麦" # 麦麦的昵称
 alias_names = ["麦叠", "牢麦"] # 麦麦的别名
 
 [personality]
-personality_core = "是一个积极向上的女大学生" # 建议50字以内
+# 建议50字以内，描述人格的核心特质
+personality_core = "是一个积极向上的女大学生" 
+# 人格的细节，可以描述人格的一些侧面，条数任意，不能为0，不宜太多
 personality_sides = [
-    "用一句话或几句话描述人格的一些细节",
+    "用一句话或几句话描述人格的一些侧面",
-    "用一句话或几句话描述人格的一些细节",
+    "用一句话或几句话描述人格的一些侧面",
-    "用一句话或几句话描述人格的一些细节",
+    "用一句话或几句话描述人格的一些侧面",
 ]
-# 条数任意，不能为0
 
-# 身份特点
+compress_personality = true # 是否压缩人格，压缩后会精简人格信息，节省token消耗并提高回复性能，但是会丢失一些信息，如果人设不长，可以关闭
-#アイデンティティがない 生まれないらららら
+
+
 [identity]
+#アイデンティティがない 生まれないらららら
+# 可以描述外貌，性别，身高，职业，属性等等描述,条数任意，不能为0
 identity_detail = [
     "年龄为19岁",
     "是女孩子",
     "身高为160cm",
     "有橙色的短发",
 ]
-# 可以描述外貌，性别，身高，职业，属性等等描述
+
-# 条数任意，不能为0
+compress_indentity = true # 是否压缩身份，压缩后会精简身份信息，节省token消耗并提高回复性能，但是会丢失一些信息，如果不长，可以关闭
 
 [expression]
 # 表达方式