"""
用户输入意图分类：区分「自然语言查数 / Text2SQL」与「寒暄、致谢、元问题」等不适合直接生成 SQL 的对话。
"""

from __future__ import annotations

import logging
import re
import unicodedata
from enum import Enum
from typing import NamedTuple, Optional

logger = logging.getLogger(__name__)


class DialogIntent(str, Enum):
    TEXT2SQL = "text2sql"
    CONVERSATION = "conversation"


class DialogClassifyResult(NamedTuple):
    intent: DialogIntent
    """若为 CONVERSATION，可展示给用户的引导文案；TEXT2SQL 时为 None。"""
    reply_suggestion: Optional[str] = None


DEFAULT_CONVERSATION_REPLY = (
    "您好，我是业务库 Text2SQL 助手。\n"
    "请用自然语言描述要查询或统计的内容（例如：查询某账户可用余额、按经纪商汇总未结算交易笔数）。\n"
    "输入 quit 或 exit 可退出。"
)

_EMPTY_INPUT_REPLY = "请输入具体的业务查询问题，或输入 quit 退出。"

# 一旦出现，倾向于按「要查数据」处理（含常见业务词，避免误判）
_SQL_OR_QUERY_HINT_RE = re.compile(
    r"(查|查询|查出|检索|统计|列出|汇总|求和|平均|分组|排序|排名|显示|导出|筛选|过滤|"
    r"多少|几个|几张|哪些|占比|同比|环比|"
    r"余额|交易|账户|持仓|报表|结算|合约|订单|流水|经纪商|对手方|证券|资金|"
    r"query|select|list|show|count|sum|avg|how\s+many|statistics|\bfrom\b|\bwhere\b|\btable\b)",
    re.IGNORECASE,
)

_CHITCHAT_PHRASES = frozenset(
    {
        "你好",
        "您好",
        "嗨",
        "哈喽",
        "hello",
        "hi",
        "hey",
        "早上好",
        "下午好",
        "晚上好",
        "在吗",
        "在不在",
        "谢谢",
        "多谢",
        "感谢",
        "thanks",
        "thank you",
        "thx",
        "再见",
        "拜拜",
        "bye",
        "goodbye",
        "哈哈",
        "哈哈哈",
        "嗯",
        "嗯嗯",
        "好的",
        "好",
        "ok",
        "okay",
        "行",
        "收到",
        "👋",
        "😀",
        "哈哈谢谢",
    }
)

_CHITCHAT_KEYS = frozenset(p.casefold() for p in _CHITCHAT_PHRASES)

_META_QUESTION_RE = re.compile(
    r"(你是谁|你是什么|你能(做|干)什么|你会什么|怎么用|如何使用|使用说明|帮助|help\b|"
    r"什么功能|干啥的)",
    re.IGNORECASE,
)


def _normalize(text: str) -> str:
    t = unicodedata.normalize("NFKC", text or "").strip()
    t = re.sub(r"\s+", " ", t)
    return t


def _strip_trailing_punct(t: str) -> str:
    return re.sub(r"[！!。.?？,，;；:~～…、]+$", "", t).strip()


def classify_dialog(user_text: str) -> DialogClassifyResult:
    """
    对用户一轮输入做粗分类。

    策略：优先用「查询/业务」关键词锁定 TEXT2SQL；否则对短寒暄、致谢、元问题判为 CONVERSATION；
    其余默认 TEXT2SQL，避免漏判真实查询。
    """
    t = _normalize(user_text)
    if not t:
        return DialogClassifyResult(
            DialogIntent.CONVERSATION, reply_suggestion=_EMPTY_INPUT_REPLY
        )

    if _SQL_OR_QUERY_HINT_RE.search(t):
        logger.debug("[dialog] intent=text2sql (query/business hint)")
        return DialogClassifyResult(DialogIntent.TEXT2SQL, None)

    core = _strip_trailing_punct(t)
    if core.casefold() in _CHITCHAT_KEYS:
        logger.debug("[dialog] intent=conversation (chitchat phrase)")
        return DialogClassifyResult(
            DialogIntent.CONVERSATION, reply_suggestion=DEFAULT_CONVERSATION_REPLY
        )

    if _META_QUESTION_RE.search(t):
        logger.debug("[dialog] intent=conversation (meta question)")
        return DialogClassifyResult(
            DialogIntent.CONVERSATION,
            reply_suggestion=DEFAULT_CONVERSATION_REPLY,
        )

    logger.debug("[dialog] intent=text2sql (default)")
    return DialogClassifyResult(DialogIntent.TEXT2SQL, None)