"""推理链轨迹存储（T3：整体项目部分拆解·先行实现）。

内存环形缓冲（零依赖）：记录每次请求的完整推理链（两级路由决策、
三级子领域、规则触发、任务拆解、节点执行、质量评分），支持按请求 ID 追溯。
可解释性 = 专家系统 vs 黑盒 LLM 的差异化护城河。
"""
from __future__ import annotations

import threading
from collections import deque
from typing import Any, Deque, Dict, Optional


class TraceStore:
    """请求推理链轨迹存储（线程安全，环形淘汰）。"""

    def __init__(self, max_entries: int = 1000):
        self._max = max_entries
        self._entries: Dict[str, Dict[str, Any]] = {}
        self._order: Deque[str] = deque(maxlen=max_entries)
        self._lock = threading.Lock()

    def put(self, request_id: str, trace: Dict[str, Any]) -> None:
        with self._lock:
            if request_id in self._entries:
                self._entries[request_id] = trace
                return
            if len(self._entries) >= self._max:
                # 环形淘汰最旧
                while self._order:
                    oldest = self._order.popleft()
                    if oldest in self._entries:
                        del self._entries[oldest]
                        break
            self._entries[request_id] = trace
            self._order.append(request_id)

    def get(self, request_id: str) -> Optional[Dict[str, Any]]:
        with self._lock:
            return self._entries.get(request_id)

    def size(self) -> int:
        with self._lock:
            return len(self._entries)

    def clear(self) -> None:
        with self._lock:
            self._entries.clear()
            self._order.clear()