# ============================================================
# 对话历史规范化（moduleId: core-context, 可重生 ✅）
# 只做纯数据整形：把网关收到的历史消息收敛成 {role, text}。
# 多轮语义理解统一交给 Pi Agent，本模块不做任何规则判断。
# ============================================================
from __future__ import annotations

from typing import Any

HistoryItem = dict[str, str]  # {role: user|agent, text: str}


def normalize_history(raw: list[Any] | None, *, limit: int = 12) -> list[HistoryItem]:
    out: list[HistoryItem] = []
    for m in raw or []:
        if not isinstance(m, dict):
            continue
        role = str(m.get("role") or "")
        if role in ("assistant", "bot", "ai"):
            role = "agent"
        if role not in ("user", "agent"):
            continue
        text = str(m.get("text") or m.get("content") or "").strip()
        if not text:
            continue
        out.append({"role": role, "text": text})
    return out[-limit:]