49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
"""
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极简 Agent 状态定义 - 只保留真正需要的字段
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保留的核心字段：
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- messages: 对话历史（LangGraph 必需）
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- user_id: 用户标识
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- 记忆相关：turns_since_last_summary, memory_context
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- 安全限制：current_step, max_steps
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- 统计：llm_calls, last_token_usage, last_elapsed_time
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"""
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from typing import Annotated, Sequence, Optional, Dict, Any, List
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from dataclasses import dataclass, field
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from langgraph.graph import add_messages
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from langchain_core.messages import BaseMessage
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@dataclass
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class AgentState:
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"""Agent 状态"""
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# ========== 核心持久化字段（必需） ==========
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messages: Annotated[Sequence[BaseMessage], add_messages] = field(default_factory=list)
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user_id: str = ""
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# ========== 安全限制字段（防止无限循环） ==========
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max_steps: int = 10
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current_step: int = 0
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# ========== 记忆相关字段（保留） ==========
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turns_since_last_summary: int = 0
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memory_context: str = ""
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# ========== 统计字段（保留） ==========
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llm_calls: int = 0
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last_token_usage: Dict[str, Any] = field(default_factory=dict)
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last_elapsed_time: float = 0.0
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# ========== 新增字段: 工具调用历史 ==========
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tool_call_history: List[dict] = field(default_factory=list)
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tool_result_history: List[str] = field(default_factory=list)
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# ========== 新增字段: 停止控制 ==========
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stop: bool = False
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stop_reason: str = ""
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# ========== 新增字段: 本轮使用的工具 ==========
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tools_used: List[str] = field(default_factory=list)
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