彻底重构状态系统：整合所有旧状态到 MainGraphState，修复所有节点

backend/app/main_graph/state.py

@@ -10,17 +10,9 @@ from app.main_graph.graph import add_messages
 from langchain_core.messages import BaseMessage
 
 
-# ========== 兼容旧代码的类型 ==========
-class MessagesState(TypedDict):
-    """旧的MessagesState类型（保留兼容性）"""
-    messages: Annotated[Sequence[BaseMessage], add_messages]
-
-
-class GraphContext(TypedDict):
-    """旧的GraphContext类型（保留兼容性）"""
-    llm_calls: int
-    memory_context: str
-    system_prompt: str
+# ========== 兼容性注释（旧代码已移除，状态已整合到 MainGraphState） ==========
+# 旧的 MessagesState 和 GraphContext 已完全整合到 MainGraphState
+# 不再需要单独的类型定义
 
 
 # ========== 新的类型 ==========
@@ -57,49 +49,52 @@ class ErrorRecord:
 @dataclass
 class MainGraphState:
     """
-    主图状态 - React 循环推理版本
+    主图状态 - 整合了旧 MessagesState 的所有字段
     
     包含：
-    1. 旧代码的MessagesState兼容性字段
-    2. React 推理控制字段
-    3. 循环和错误处理
-    4. 子图结果占位
-    5. 用户信息
+    - 旧代码的 MessagesState 兼容性字段
+    - React 推理控制字段
+    - 循环和错误处理
+    - 子图结果占位
+    - 用户信息
     """
-    # ========== 兼容性字段（保留旧的MessagesState） ==========
+    # ========== 旧 MessagesState 兼容性字段 ==========
     messages: Annotated[Sequence[BaseMessage], add_messages] = field(default_factory=list)
     llm_calls: int = 0
     memory_context: str = ""
     system_prompt: str = ""
+    turns_since_last_summary: int = 0  # 新增：来自旧状态
+    last_token_usage: Dict[str, Any] = field(default_factory=dict)  # 新增：来自旧状态
+    last_elapsed_time: float = 0.0  # 新增：来自旧状态
     
     # ========== 主图控制字段 ==========
-    user_query: str = ""  # 用户当前查询
-    current_action: CurrentAction = CurrentAction.NONE  # 当前操作
-    intent_confidence: float = 0.0  # 意图识别置信度
+    user_query: str = ""
+    current_action: CurrentAction = CurrentAction.NONE
+    intent_confidence: float = 0.0
     
     # ========== React 推理专用字段 ==========
-    reasoning_step: int = 0  # 当前推理步数
-    max_steps: int = 40  # 最大推理步数
-    last_action: str = ""  # 上一步动作
-    reasoning_history: List[Dict[str, Any]] = field(default_factory=list)  # 推理历史
+    reasoning_step: int = 0
+    max_steps: int = 40
+    last_action: str = ""
+    reasoning_history: List[Dict[str, Any]] = field(default_factory=list)
     
     # ========== RAG 相关字段 ==========
-    rag_context: str = ""  # RAG 检索到的上下文
-    rag_retrieved: bool = False  # 是否已经检索过
-    rag_docs: List[Dict[str, Any]] = field(default_factory=list)  # 检索到的文档
+    rag_context: str = ""
+    rag_retrieved: bool = False
+    rag_docs: List[Dict[str, Any]] = field(default_factory=list)
     
-    # ========== 联网搜索相关字段 ⭐ 新增 ==========
-    web_search_results: List[str] = field(default_factory=list)  # 联网搜索结果
+    # ========== 联网搜索相关字段 ==========
+    web_search_results: List[str] = field(default_factory=list)
     
     # ========== 错误处理字段 ==========
-    errors: List[ErrorRecord] = field(default_factory=list)  # 错误列表
-    current_error: Optional[ErrorRecord] = None  # 当前错误
-    retry_action: Optional[str] = None  # 重试动作
+    errors: List[ErrorRecord] = field(default_factory=list)
+    current_error: Optional[ErrorRecord] = None
+    retry_action: Optional[str] = None
     
     # ========== 子图结果占位 ==========
-    news_result: Optional[Dict[str, Any]] = None  # 资讯子图结果
-    dictionary_result: Optional[Dict[str, Any]] = None  # 词典子图结果
-    contact_result: Optional[Dict[str, Any]] = None  # 通讯录子图结果
+    news_result: Optional[Dict[str, Any]] = None
+    dictionary_result: Optional[Dict[str, Any]] = None
+    contact_result: Optional[Dict[str, Any]] = None
     
     # ========== 用户信息 ==========
     user_id: str = ""