feat: 优化后的流式方案：双协程 + 结束哨兵 + turn/phase 元数据

backend/app/main_graph/main_graph_builder.py

@@ -1,11 +1,12 @@
 """
-极简 Agent 主图 - 用 LangGraph 原生 create_react_agent + 记忆节点
+极简 Agent 主图 - 自己的节点结构，更好控制流式
 """
 
-from langgraph.prebuilt import create_react_agent
 from langgraph.graph import StateGraph, START, END
+from langgraph.prebuilt import ToolNode
 from ..state import AgentState
 from ..nodes.memory_trigger import memory_trigger_node, set_mem0_client
+from ..nodes.agent import create_agent_node
 from backend.app.logger import info, warning
 from backend.app.tools import ALL_TOOLS
 
@@ -16,7 +17,7 @@ def build_agent_graph(
     max_steps: int = 10
 ):
     """
-    构建包含记忆节点的 react agent 图
+    构建包含记忆节点的 Agent 图
 
     Args:
         chat_services: 模型服务字典
@@ -24,7 +25,7 @@ def build_agent_graph(
         max_steps: 最大步数限制
 
     Returns:
-        编译好的 graph
+        构建好的 StateGraph（未编译）
     """
     # 获取主模型
     primary_model = chat_services.get("primary", next(iter(chat_services.values())))
@@ -37,7 +38,8 @@ def build_agent_graph(
     async def init_state_node(state: AgentState):
         info("[Init State] 初始化状态，重置步数")
         return {
-            "current_step": 0
+            "current_step": 0,
+            "max_steps": max_steps
         }
 
     # ========== 2. 记忆节点（可选） ==========
@@ -49,21 +51,39 @@ def build_agent_graph(
         except Exception as e:
             info(f"[Graph Builder] 记忆节点初始化失败: {e}")
 
-    # ========== 3. 创建 react agent 子图 ==========
-    agent_runnable = create_react_agent(primary_model, ALL_TOOLS)
+    # ========== 3. 核心节点 ==========
+    llm_with_tools = primary_model.bind_tools(ALL_TOOLS)
+    agent_node_fn = create_agent_node(llm_with_tools, primary_model)
+    tool_node_fn = ToolNode(ALL_TOOLS)
 
-    # ========== 4. 构建主图 ==========
+    # ========== 4. 条件边判断函数 ==========
+    def should_continue(state: AgentState):
+        """判断是继续调用工具还是结束"""
+        messages = state.messages
+        last_message = messages[-1] if messages else None
+
+        if last_message and hasattr(last_message, 'tool_calls') and last_message.tool_calls:
+            return "tools"
+
+        return "finalize"
+
+    # ========== 5. 完成节点 ==========
+    async def finalize_node_simple(state: AgentState):
+        info("[Finalize] 进入完成节点")
+        return {}
+
+    # ========== 6. 构建图 ==========
     graph = StateGraph(AgentState)
 
     graph.add_node("init_state", init_state_node)
     if retrieve_memory_node:
         graph.add_node("retrieve_memory", retrieve_memory_node)
     graph.add_node("memory_trigger", memory_trigger_node)
+    graph.add_node("agent", agent_node_fn)
+    graph.add_node("tools", tool_node_fn)
+    graph.add_node("finalize", finalize_node_simple)
 
-    # 直接把 create_react_agent 的可运行对象作为节点
-    graph.add_node("agent", agent_runnable)
-
-    # ========== 边的连接 ==========
+    # ========== 7. 边的连接 ==========
     graph.add_edge(START, "init_state")
 
     if retrieve_memory_node:
@@ -73,7 +93,18 @@ def build_agent_graph(
         graph.add_edge("init_state", "memory_trigger")
 
     graph.add_edge("memory_trigger", "agent")
-    graph.add_edge("agent", END)
 
-    info("✅ [Graph Builder] 极简 Agent 图构建完成（用 create_react_agent）")
+    graph.add_conditional_edges(
+        "agent",
+        should_continue,
+        {
+            "tools": "tools",
+            "finalize": "finalize"
+        }
+    )
+
+    graph.add_edge("tools", "agent")
+    graph.add_edge("finalize", END)
+
+    info("✅ [Graph Builder] 极简 Agent 图构建完成")
     return graph