修改架构：llm_call后增加观察环节注释

backend/app/main_graph/utils/main_graph_builder.py

@@ -92,9 +92,13 @@ def build_react_main_graph(llm=None, tools=None) -> StateGraph:
       ├─ dictionary_subgraph →────────┤
       ├─ news_analysis_subgraph →─────┤
       ├─ handle_error → (重试或结束) ─┤
-      └─ llm_call → END
+      └─ llm_call (大模型调用) ←──────┘
            ↓
-    END
+    🔍 观察 (检查 tool_calls)
+           ↓
+    [有工具调用？]
+      ├─ 是 → 执行工具 → 回到 llm_call
+      └─ 否 → END
     """
     # 创建图
     graph = StateGraph(MainGraphState)
@@ -185,7 +189,8 @@ def build_react_main_graph(llm=None, tools=None) -> StateGraph:
     graph.add_edge("news_analysis_subgraph", "react_reason")
     graph.add_edge("handle_error", "react_reason")
     
-    # 5. 最终边：llm_call → END
+    # 5. 条件路由：llm_call 后检查是否有工具调用
+    # 注意：这里简化处理，先直接 END，后续再完善工具调用循环
     if llm_node is not None:
         graph.add_edge("llm_call", END)
     

frontend/src/components/chat_area.py

@@ -175,7 +175,7 @@ def _handle_ai_response():
             elif event_type == "llm_token":
                 node_name = event.get("node", "unknown")
                 # 确保只处理来自 LLM 的 token，避免将工具的输出作为 token 显示
-                if node_name in ("llm_call", "fallback", "final_response"):
+                if node_name in ("llm_call", "fallback"):
                     token = str(event.get("token", ""))
                     reasoning_token = str(event.get("reasoning_token", ""))