"""
访谈轮次编排（方案 A）：由服务端显式给出 turn_mode / 主槽 / 挂钩摘录，
减少仅靠长 prompt 软约束时模型「随便问、不往回忆录引」的漂移。
"""

from __future__ import annotations

from dataclasses import dataclass
from typing import Literal

from app.agents.chat.prompts_conversation import SLOT_NAME_MAP
from app.agents.stage_constants import STAGE_SLOT_KEYS

InterviewTurnMode = Literal["emotion_first", "memoir_push", "follow_user_only"]


@dataclass(frozen=True)
class InterviewTurnPlan:
    """单轮访谈的硬目标（供注入 system prompt 顶部，优先级高于一般性建议）。"""

    mode: InterviewTurnMode
    anchor_slot_key: str | None
    anchor_slot_readable: str
    anchor_snippet: str


def primary_empty_slot(stage: str, empty_slots: list[str]) -> str | None:
    """按 STAGE_SLOT_KEYS 顺序取第一个仍空的槽。"""
    if not empty_slots:
        return None
    order = STAGE_SLOT_KEYS.get(stage, ())
    for key in order:
        if key in empty_slots:
            return key
    return empty_slots[0]


def _strip_scene_hint(memory_evidence_text: str) -> str:
    raw = (memory_evidence_text or "").strip()
    if "[场景氛围提示" in raw:
        raw = raw.split("[场景氛围提示", 1)[0].strip()
    return raw


def extract_anchor_snippet(
    *,
    memory_evidence_text: str,
    user_message: str,
    max_chars: int = 180,
) -> str:
    """优先记忆摘录，其次用户原话（用于追问挂钩，非事实断言）。"""
    mem = _strip_scene_hint(memory_evidence_text)
    if mem and len(mem) >= 4:
        return mem[:max_chars].strip()
    um = (user_message or "").strip()
    if len(um) >= 10:
        return um[:max_chars].strip()
    return ""


_EMOTION_MARKERS: tuple[str, ...] = (
    "哭",
    "难受",
    "委屈",
    "害怕",
    "后悔",
    "恨",
    "舍不得",
    "崩溃",
    "绝望",
    "心疼",
    "哽咽",
    "咽不下",
    "睡不着",
    "想哭",
    "好难",
    "太难了",
    "挺不住",
    "扛不住",
    "放不下",
    "意难平",
)


def _is_emotion_heavy(text: str) -> bool:
    t = (text or "").strip()
    if not t:
        return False
    if any(m in t for m in _EMOTION_MARKERS):
        return True
    if (
        len(t) >= 40
        and ("！" in t or "!" in t)
        and (".." in t or "…" in t or "唉" in t)
    ):
        return True
    return False


def plan_interview_turn(
    *,
    current_stage: str,
    empty_slots: list[str],
    normalized_user_message: str,
    memory_evidence_text: str,
    stage_switched_this_turn: bool,
) -> InterviewTurnPlan:
    """
    粗规则（可迭代）：
    - 情绪浓：先共情，不强推叙述槽搜集问。
    - 刚切换人生阶段：跟着用户节奏，不做「新阶段问卷首开」。
    - 当前阶段无空槽：深度跟进，不重启盘点。
    - 默认：memoir_push，锁一个主槽 + 挂钩摘录。
    """
    snippet = extract_anchor_snippet(
        memory_evidence_text=memory_evidence_text,
        user_message=normalized_user_message,
    )

    if _is_emotion_heavy(normalized_user_message):
        slot = primary_empty_slot(current_stage, empty_slots)
        readable = (
            SLOT_NAME_MAP.get(slot, slot or "")
            if slot
            else "（情绪优先时可暂不强绑某一槽位）"
        )
        return InterviewTurnPlan(
            mode="emotion_first",
            anchor_slot_key=slot,
            anchor_slot_readable=readable,
            anchor_snippet=snippet,
        )

    if stage_switched_this_turn:
        return InterviewTurnPlan(
            mode="follow_user_only",
            anchor_slot_key=None,
            anchor_slot_readable="（刚自然谈到本阶段，先顺着对方语势，勿问卷式首开）",
            anchor_snippet=snippet,
        )

    if not empty_slots:
        return InterviewTurnPlan(
            mode="follow_user_only",
            anchor_slot_key=None,
            anchor_slot_readable="（本阶段主要叙述槽已有素材）请 depth-first：接续画面或情绪线，别重启童年在哪长大式盘点",
            anchor_snippet=snippet,
        )

    slot = primary_empty_slot(current_stage, empty_slots)
    assert slot is not None
    return InterviewTurnPlan(
        mode="memoir_push",
        anchor_slot_key=slot,
        anchor_slot_readable=SLOT_NAME_MAP.get(slot, slot),
        anchor_snippet=snippet,
    )


def format_interview_turn_directive_block(plan: InterviewTurnPlan) -> str:
    """注入 guided prompt 顶部的硬指令块。"""
    snippet_line = (
        plan.anchor_snippet
        if plan.anchor_snippet
        else "（无可用摘录时，必须从用户本轮原话里抽词作挂钩，禁止编造）"
    )

    if plan.mode == "emotion_first":
        mode_rules = (
            "- **情绪优先**：本轮以承接、并肩与安全感为主，**不要**为推进「叙述槽大纲」而追加信息搜集型追问。\n"
            "- 若末尾带问，只能是**贴着用户当前情绪或原词**的极轻一句；禁止切到盘点式下一题。\n"
            "- 参考主槽「"
            + plan.anchor_slot_readable
            + "」仅供你心里知道后续方向，**不要**在本轮用问卷口吻硬推该槽。"
        )
    elif plan.mode == "follow_user_only":
        mode_rules = (
            "- **跟话头**：本轮禁止问卷式首开、禁止重启式盘点；顺着用户刚展开的画面、人物或情绪自然往下。\n"
            "- 若带问句，最多**一个**，且必须**从用户原词或下面摘录**长出来，禁止空泛「还有吗」。"
        )
    else:
        mode_rules = (
            "- **回忆推进（memoir_push）**：对用户可见回复中须有**恰好一个**开放式回忆追问，\n"
            "  且意图明显在补足下面「主追问方向」；问句必须挂住**挂钩摘录**或**用户本轮原词**（二者至少其一）。\n"
            "- 禁止用日常寒暄替代该追问；仍遵守全篇「最多一个问句」「禁止晚会硬切」。"
        )

    return f"""## 本轮编排指令（硬规则，优先于后文一般性建议）
{mode_rules}
- **主追问方向（叙述槽）**：{plan.anchor_slot_readable}
- **挂钩摘录**（仅作衔接线索，**不是**用户本轮新说的内容；禁止写成就等于用户刚讲的原话）：{snippet_line}
"""


__all__ = [
    "InterviewTurnMode",
    "InterviewTurnPlan",
    "extract_anchor_snippet",
    "format_interview_turn_directive_block",
    "plan_interview_turn",
    "primary_empty_slot",
]