"""
极简 Agent 状态定义 - 只保留真正需要的字段

保留的核心字段：
- messages: 对话历史（LangGraph 必需）
- user_id: 用户标识
- 记忆相关：turns_since_last_summary, memory_context
- 安全限制：current_step, max_steps
- 统计：llm_calls, last_token_usage, last_elapsed_time
"""

from typing import Annotated, Sequence, Optional, Dict, Any, List
from dataclasses import dataclass, field
from langgraph.graph import add_messages
from langchain_core.messages import BaseMessage


@dataclass
class AgentState:
    """Agent 状态"""
    
    # ========== 核心持久化字段（必需） ==========
    messages: Annotated[Sequence[BaseMessage], add_messages] = field(default_factory=list)
    user_id: str = ""
    
    # ========== 安全限制字段（防止无限循环） ==========
    max_steps: int = 10
    current_step: int = 0
    
    # ========== 记忆相关字段（保留） ==========
    turns_since_last_summary: int = 0
    memory_context: str = ""
    
    # ========== 统计字段（保留） ==========
    llm_calls: int = 0
    last_token_usage: Dict[str, Any] = field(default_factory=dict)
    last_elapsed_time: float = 0.0

    # ========== 新增字段: 工具调用历史 ==========
    tool_call_history: List[dict] = field(default_factory=list)
    tool_result_history: List[str] = field(default_factory=list)

    # ========== 新增字段: 停止控制 ==========
    stop: bool = False
    stop_reason: str = ""

    # ========== 新增字段: 本轮使用的工具 ==========
    tools_used: List[str] = field(default_factory=list)