feat 增加推荐对话可控参数

src/server/agent/agents.py

@@ -42,9 +42,10 @@ async def designer_node(state: AgentState, config: RunnableConfig):
     system_text = get_agent_prompt("designer")
 
     system_prompt = SystemMessage(content=system_text)
+    should_suggest = len(state["messages"]) % 5 == 0
     # 改为异步调用 ainvoke
     response = await model.ainvoke([system_prompt] + messages)
-    return {"messages": [response]}
+    return {"messages": [response], "require_suggestion": should_suggest}
 
 
 # --- 2. Researcher Agent (情报专家) ---

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)

src/server/agent/state.py

@@ -6,4 +6,5 @@ class AgentState(TypedDict):
     # messages 存储完整的对话历史，operator.add 表示新消息是追加而不是覆盖
     messages: Annotated[Sequence[BaseMessage], operator.add]
     # next 存储 Supervisor 决定的下一步是谁
-    next: str
+    next: str
+    require_suggestion: bool  # 是否需要建议按钮