优化：复用 hybrid_router 的推理结果，避免重复 LLM 调用

backend/app/main_graph/nodes/hybrid_router.py

@@ -30,6 +30,7 @@ class HybridRouterResult:
     suggested_tools: list = field(default_factory=list)
     path: str = "react_loop"  # fast_chitchat / fast_rag / fast_tool / react_loop
     reasoning: str = ""
+    reasoning_result: Optional[ReasoningResult] = None  # 保存完整的 ReasoningResult，用于复用！
 
 
 # ========== 规则配置 ==========
@@ -87,7 +88,8 @@ def _map_reasoning_to_router(reasoning_result: ReasoningResult) -> HybridRouterR
         confidence=reasoning_result.confidence,
         suggested_tools=suggested_tools,
         path=path,
-        reasoning=reasoning_result.reasoning
+        reasoning=reasoning_result.reasoning,
+        reasoning_result=reasoning_result  # 保存完整结果！
     )
 
 

backend/app/main_graph/nodes/reasoning.py

@@ -7,8 +7,8 @@ from typing import Optional
 from datetime import datetime
 from langchain_core.runnables.config import RunnableConfig
 
-from backend.app.core.intent import react_reason_async, ReasoningResult
-from ...main_graph.state import MainGraphState
+from backend.app.core.intent import react_reason_async, ReasoningResult, ReasoningAction
+from ..state import MainGraphState
 from backend.app.logger import info
 from ._utils import dispatch_custom_event, make_react_event
 
@@ -20,6 +20,55 @@ async def react_reason_node(state: MainGraphState, config: Optional[RunnableConf
 
     info(f"[推理] 第 {state.reasoning_step} 次推理开始")
 
+    # ==================================================
+    # 优化：如果是第一次推理，检查 hybrid_router 的结果！
+    # 避免重复推理！
+    # ==================================================
+    if state.reasoning_step == 1 and state.hybrid_router.decision and state.hybrid_router.decision.reasoning_result:
+        # 有保存的推理结果，直接复用！
+        decision = state.hybrid_router.decision
+        result: ReasoningResult = decision.reasoning_result
+
+        info(f"[推理] 第1次推理，复用 hybrid_router 结果: action={result.action.name}, confidence={result.confidence}")
+        if result.reasoning:
+            info(f"[推理] 推理过程: {result.reasoning}")
+
+        # 记录推理历史
+        state.reasoning_history.append({
+            "step": state.reasoning_step,
+            "action": result.action.name,
+            "confidence": result.confidence,
+            "reasoning": result.reasoning,
+            "timestamp": datetime.now().isoformat()
+        })
+
+        # 更新状态
+        state.react_reasoning.last_reasoning = {
+            "action": result.action.name,
+            "confidence": result.confidence,
+            "reasoning": result.reasoning
+        }
+        state.react_reasoning.reasoning_result = result
+        state.last_action = result.action.name
+
+        # 发送推理事件
+        await dispatch_custom_event(
+            "react_reasoning",
+            make_react_event(
+                state.reasoning_step,
+                result.action.name,
+                result.confidence,
+                result.reasoning
+            ),
+            config
+        )
+
+        return state
+
+    # ==================================================
+    # 原来的逻辑（第二次推理或没有保存结果时使用）
+    # ==================================================
+
     # 步骤1: 准备上下文
     context = {
         "retrieved_docs": state.rag_docs,
@@ -47,7 +96,7 @@ async def react_reason_node(state: MainGraphState, config: Optional[RunnableConf
         "timestamp": datetime.now().isoformat()
     })
 
-    # 步骤3: 更新状态 - 只使用新的结构化字段
+    # 步骤4: 更新状态 - 只使用新的结构化字段
     state.react_reasoning.last_reasoning = {
         "action": result.action.name,
         "confidence": result.confidence,