feat：增加了工作记忆

src/chat/heart_flow/observation/chatting_observation.py

@@ -120,12 +120,12 @@ class ChattingObservation(Observation):
         for message in reverse_talking_message:
             if message["processed_plain_text"] == text:
                 find_msg = message
-                logger.debug(f"找到的锚定消息：find_msg: {find_msg}")
+                # logger.debug(f"找到的锚定消息：find_msg: {find_msg}")
                 break
             else:
                 similarity = difflib.SequenceMatcher(None, text, message["processed_plain_text"]).ratio()
                 msg_list.append({"message": message, "similarity": similarity})
-            logger.debug(f"对锚定消息检查：message: {message['processed_plain_text']},similarity: {similarity}")
+            # logger.debug(f"对锚定消息检查：message: {message['processed_plain_text']},similarity: {similarity}")
         if not find_msg:
             if msg_list:
                 msg_list.sort(key=lambda x: x["similarity"], reverse=True)

src/chat/heart_flow/observation/memory_observation.py

@@ -1,55 +0,0 @@
-from src.chat.heart_flow.observation.observation import Observation
-from datetime import datetime
-from src.common.logger_manager import get_logger
-import traceback
-
-# Import the new utility function
-from src.chat.memory_system.Hippocampus import HippocampusManager
-import jieba
-from typing import List
-
-logger = get_logger("memory")
-
-
-class MemoryObservation(Observation):
-    def __init__(self, observe_id):
-        super().__init__(observe_id)
-        self.observe_info: str = ""
-        self.context: str = ""
-        self.running_memory: List[dict] = []
-
-    def get_observe_info(self):
-        for memory in self.running_memory:
-            self.observe_info += f"{memory['topic']}:{memory['content']}\n"
-        return self.observe_info
-
-    async def observe(self):
-        # ---------- 2. 获取记忆 ----------
-        try:
-            # 从聊天内容中提取关键词
-            chat_words = set(jieba.cut(self.context))
-            # 过滤掉停用词和单字词
-            keywords = [word for word in chat_words if len(word) > 1]
-            # 去重并限制数量
-            keywords = list(set(keywords))[:5]
-
-            logger.debug(f"取的关键词: {keywords}")
-
-            # 调用记忆系统获取相关记忆
-            related_memory = await HippocampusManager.get_instance().get_memory_from_topic(
-                valid_keywords=keywords, max_memory_num=3, max_memory_length=2, max_depth=3
-            )
-
-            logger.debug(f"获取到的记忆: {related_memory}")
-
-            if related_memory:
-                for topic, memory in related_memory:
-                    # 将记忆添加到 running_memory
-                    self.running_memory.append(
-                        {"topic": topic, "content": memory, "timestamp": datetime.now().isoformat()}
-                    )
-                    logger.debug(f"添加新记忆: {topic} - {memory}")
-
-        except Exception as e:
-            logger.error(f"观察 记忆时出错: {e}")
-            logger.error(traceback.format_exc())

src/chat/heart_flow/observation/structure_observation.py

@@ -0,0 +1,32 @@
+from datetime import datetime
+from src.common.logger_manager import get_logger
+
+# Import the new utility function
+
+logger = get_logger("observation")
+
+
+# 所有观察的基类
+class StructureObservation:
+    def __init__(self, observe_id):
+        self.observe_info = ""
+        self.observe_id = observe_id
+        self.last_observe_time = datetime.now().timestamp()  # 初始化为当前时间
+        self.history_loop = []
+        self.structured_info = []
+
+    def get_observe_info(self):
+        return self.structured_info
+
+    def add_structured_info(self, structured_info: dict):
+        self.structured_info.append(structured_info)
+
+    async def observe(self):
+        observed_structured_infos = []
+        for structured_info in self.structured_info:
+            if structured_info.get("ttl") > 0:
+                structured_info["ttl"] -= 1
+            observed_structured_infos.append(structured_info)
+            logger.debug(f"观察到结构化信息仍旧在: {structured_info}")
+
+        self.structured_info = observed_structured_infos

src/chat/heart_flow/observation/working_observation.py

@@ -2,33 +2,33 @@
 # 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
 from datetime import datetime
 from src.common.logger_manager import get_logger
-
+from src.chat.focus_chat.working_memory.working_memory import WorkingMemory
+from src.chat.focus_chat.working_memory.memory_item import MemoryItem
+from typing import List
 # Import the new utility function
 
 logger = get_logger("observation")
 
 
 # 所有观察的基类
-class WorkingObservation:
-    def __init__(self, observe_id):
+class WorkingMemoryObservation:
+    def __init__(self, observe_id, working_memory: WorkingMemory):
         self.observe_info = ""
         self.observe_id = observe_id
-        self.last_observe_time = datetime.now().timestamp()  # 初始化为当前时间
-        self.history_loop = []
-        self.structured_info = []
+        self.last_observe_time = datetime.now().timestamp()
+        
+        self.working_memory = working_memory
+        
+        self.retrieved_working_memory = []
 
     def get_observe_info(self):
-        return self.structured_info
+        return self.working_memory
 
-    def add_structured_info(self, structured_info: dict):
-        self.structured_info.append(structured_info)
+    def add_retrieved_working_memory(self, retrieved_working_memory: List[MemoryItem]):
+        self.retrieved_working_memory.append(retrieved_working_memory)
+        
+    def get_retrieved_working_memory(self):
+        return self.retrieved_working_memory
 
     async def observe(self):
-        observed_structured_infos = []
-        for structured_info in self.structured_info:
-            if structured_info.get("ttl") > 0:
-                structured_info["ttl"] -= 1
-            observed_structured_infos.append(structured_info)
-            logger.debug(f"观察到结构化信息仍旧在: {structured_info}")
-
-        self.structured_info = observed_structured_infos
+        pass