修改引用逻辑，修改长期记忆bug

app/nodes/finalize.py

@@ -4,15 +4,13 @@
 """
 
 from typing import Any, Dict
-from langgraph.runtime import Runtime
 from langgraph.config import get_stream_writer
 
 # 本地模块
-from app.graph.state import MessagesState, GraphContext
+from app.graph.state import MessagesState
 from app.utils.logging import log_state_change
 from app.logger import info, error
 
-
 from langchain_core.runnables.config import RunnableConfig
 
 async def finalize_node(state: MessagesState, config: RunnableConfig) -> Dict[str, Any]:

app/nodes/llm_call.py

@@ -3,21 +3,17 @@ LLM 调用节点模块
 负责调用大语言模型并处理响应
 """
 
-import asyncio
 import time
 from typing import Any, Dict
 from langchain_core.language_models import BaseLLM
 from langchain_core.messages import AIMessage
-from langchain_core.runnables import RunnableLambda
-from langgraph.runtime import Runtime
 
 # 本地模块
-from app.graph.state import MessagesState, GraphContext
-from app.prompts import create_system_prompt
-from app.utils.logging import log_state_change, print_llm_input
+from app.graph.state import MessagesState
+from app.agent.prompts import create_system_prompt
+from app.utils.logging import log_state_change
 from app.logger import debug, info, error
 
-
 def create_llm_call_node(llm: BaseLLM, tools: list):
     """
     工厂函数：创建 LLM 调用节点

app/nodes/memory_trigger.py

@@ -0,0 +1,38 @@
+from typing import Any, Dict
+from langchain_core.runnables.config import RunnableConfig
+from app.graph.state import MessagesState
+from app.memory.mem0_client import Mem0Client
+from app.logger import info
+
+# 全局变量，在 GraphBuilder 中注入
+_mem0_client: Mem0Client = None
+
+def set_mem0_client(client: Mem0Client):
+    global _mem0_client
+    _mem0_client = client
+
+async def memory_trigger_node(state: MessagesState, config: RunnableConfig) -> Dict[str, Any]:
+    """检测用户消息中的记忆指令，若命中则主动调用 Mem0 存储"""
+    if _mem0_client is None:
+        return {}
+
+    messages = state.get("messages", [])
+    if not messages:
+        return {}
+
+    last_msg = messages[-1]
+    content = last_msg.content if hasattr(last_msg, 'content') else str(last_msg)
+
+    # 触发词（可自行扩展）
+    trigger_words = ["记住", "记下", "保存", "备忘", "记录下", "别忘了"]
+    if any(word in content for word in trigger_words):
+        user_id = config.get("metadata", {}).get("user_id", "default_user")
+        # 确保 Mem0 已初始化
+        if not _mem0_client._initialized:
+            await _mem0_client.initialize()
+        # 将用户消息作为事实来源提交给 Mem0
+        mem0_messages = [{"role": "user", "content": content}]
+        await _mem0_client.add_memories(mem0_messages, user_id=user_id)
+        info(f"📌 检测到记忆指令，已主动触发 Mem0 存储")
+
+    return {}  # 不修改状态

app/nodes/summarize.py

@@ -4,15 +4,13 @@
 """
 
 from typing import Any, Dict
-from langgraph.runtime import Runtime
 
 # 本地模块
-from app.graph.state import MessagesState, GraphContext
+from app.graph.state import MessagesState
 from app.memory.mem0_client import Mem0Client
 from app.utils.logging import log_state_change
 from app.logger import debug, info, error, warning
 
-
 def create_summarize_node(mem0_client: Mem0Client):
     """
     工厂函数：创建记忆存储节点

app/nodes/tool_call.py

@@ -6,15 +6,13 @@
 import asyncio
 from typing import Any, Dict
 from langchain_core.messages import AIMessage, ToolMessage
-from langgraph.runtime import Runtime
 from langgraph.config import get_stream_writer
 
 # 本地模块
-from app.graph.state import MessagesState, GraphContext
+from app.graph.state import MessagesState
 from app.utils.logging import log_state_change
 from app.logger import debug, info
 
-
 def create_tool_call_node(tools_by_name: Dict[str, Any]):
     """
     工厂函数：创建工具执行节点