feat 增加推荐对话可控参数

src/server/agent/graph.py

@@ -18,7 +18,7 @@ from langgraph.checkpoint.mongodb import MongoDBSaver
 # 定义路由的输出结构，强制 LLM 选择一个
 class RouteResponse(BaseModel):
     # 将 FINISH 替换或增加 Suggester
-    next: Literal["Designer", "Researcher", "Visualizer", "Suggester"]
+    next: Literal["Designer", "Researcher", "Visualizer", "Suggester", "FINISH"]
 
 
 creds = service_account.Credentials.from_service_account_file(
@@ -42,7 +42,13 @@ def supervisor_node(state: AgentState):
     # --- 拦截逻辑修改 ---
     # 如果专家已经回复完了（AIMessage 且无工具调用），则交给 Suggester 生成按钮
     if isinstance(last_message, AIMessage) and not last_message.tool_calls:
-        return {"next": "Suggester"}
+        should_go_to_suggester = state.get("require_suggestion", False)
+
+        # 如果符合建议条件
+        if should_go_to_suggester:
+            return {"next": "Suggester"}
+        else:
+            return {"next": "FINISH"}
 
     system_prompt = """你是家具设计主管。分配任务给专家：
     - Designer: 设计建议、参数细化。
@@ -74,7 +80,8 @@ workflow.add_conditional_edges(
         "Designer": "Designer",
         "Researcher": "Researcher",
         "Visualizer": "Visualizer",
-        "Suggester": "Suggester"  # 原本的 FINISH 现在指向 Suggester
+        "Suggester": "Suggester",  # 原本的 FINISH 现在指向 Suggester
+        "FINISH": END  # 直接结束，不给建议
     }
 )
 
@@ -82,8 +89,7 @@ workflow.add_conditional_edges(
 workflow.add_edge("Designer", "Supervisor")
 workflow.add_edge("Researcher", "Supervisor")
 workflow.add_edge("Visualizer", "Supervisor")
-
-# 重点：Suggester 是整个流程的终点
+# 重点：Suggester 可以是整个流程的终点
 workflow.add_edge("Suggester", END)
 
 client = MongoClient(MONGO_URI)