整合旧图和新图：添加完整的记忆检索、总结和完成流程

backend/app/agent/agent_service.py

@@ -13,7 +13,7 @@ from app.main_graph.config import set_stream_writer
 from ..model_services.chat_services import get_all_chat_services, LocalVLLMChatProvider
 from app.main_graph.utils.rag_initializer import init_rag_tool
 from app.core.intent_classifier import get_intent_classifier
-from app.logger import info, warning
+from app.logger import info, warning, error
 from app.main_graph.state import MainGraphState, CurrentAction
 
 
@@ -27,8 +27,19 @@ class AIAgentService:
         self.intent_classifier = get_intent_classifier()
         # RAG 管道（可选，需要时设置）
         self.rag_pipeline = None
+        # Mem0 客户端
+        self.mem0_client = None
 
     async def initialize(self):
+        # 0. 初始化 Mem0 客户端
+        from app.memory.mem0_client import Mem0Client
+        # 创建一个临时的 LLM 用于 Mem0（用第一个可用的）
+        chat_services = get_all_chat_services()
+        temp_llm = None
+        if chat_services:
+            temp_llm = list(chat_services.values())[0]
+        self.mem0_client = Mem0Client(temp_llm)
+        
         # 1. 初始化 RAG 工具（如果需要）
         def create_local_llm():
             provider = LocalVLLMChatProvider()
@@ -42,11 +53,14 @@ class AIAgentService:
             set_global_rag_tool(rag_tool)
 
         # 2. 构建各模型的 Graph（使用新版 React 模式）
-        chat_services = get_all_chat_services()
         for name, llm in chat_services.items():
             try:
                 info(f"🔄 初始化模型 '{name}'...")
-                graph = build_react_main_graph(llm=llm, tools=self.tools).compile(checkpointer=self.checkpointer)
+                graph = build_react_main_graph(
+                    llm=llm, 
+                    tools=self.tools,
+                    mem0_client=self.mem0_client
+                ).compile(checkpointer=self.checkpointer)
                 self.graphs[name] = graph
                 info(f"✅ 模型 '{name}' 初始化成功")
             except Exception as e: