"""离线确定性抽取器：技能词表 + 版面规则，从 JD 文本抽出结构化岗位定义。

版面约定（数据集与真实主流招聘平台格式兼容）：
- “岗位名称：X”行给出岗位名称；
- 职责段（岗位职责/工作职责/工作内容/职位职责）逐条编号；
- 要求段（任职要求/岗位要求/任职条件/任职资格）出现必备技能；
- 加分段（加分项/优先考虑/优先条件）出现加分技能；
- 尾部段落（团队与福利/福利待遇/岗位福利/公司福利）不属于任何技能区，
  作为加分段的结束边界，避免福利文案中的技能词混入加分技能；
- 应用场景词表全文匹配。
每个字段都附原文证据片段，供人机协同审核防“幻觉”。
"""
from __future__ import annotations

import logging
import re

from app.extract.base import SkillMatcher, load_lexicon
from app.models import ExtractionResult, JDRecord

logger = logging.getLogger(__name__)

# 版面标题词表（生成器与抽取器共用，保证规则与数据一致）
DUTY_HEADERS = ["岗位职责", "工作职责", "工作内容", "职位职责"]
REQ_HEADERS = ["任职要求", "岗位要求", "任职条件", "任职资格"]
PREF_HEADERS = ["加分项", "优先考虑", "优先条件"]
# 尾部段落标题：出现在加分段之后的团队/福利介绍，作为版面区域结束边界
TAIL_HEADERS = ["团队与福利", "福利待遇", "岗位福利", "公司福利"]

_TITLE_RE = re.compile(r"岗位名称[:：]\s*([^\n]+)")
_NUMBER_RE = re.compile(r"^\s*(?:\d+\s*[、.．)）]|[-•·])\s*")


def _find_header(text: str, headers: list[str]) -> tuple[int, int] | None:
    """返回第一处标题的 (起, 止)，找不到返回 None。"""
    best: tuple[int, int] | None = None
    for h in headers:
        i = text.find(h)
        if i >= 0 and (best is None or i < best[0]):
            best = (i, i + len(h))
    return best


class OfflineExtractor:
    """离线确定性抽取器（默认通道，无需任何外部依赖）。"""

    name = "offline"

    def __init__(self, lexicon: dict | None = None):
        self.lexicon = lexicon or load_lexicon()
        self.matcher = SkillMatcher(self.lexicon)

    def _zones(self, text: str) -> dict[str, str]:
        """把文本切成 职责/要求/加分 三个版面区域（尾部福利段落不计入）。"""
        duty = _find_header(text, DUTY_HEADERS)
        req = _find_header(text, REQ_HEADERS)
        pref = _find_header(text, PREF_HEADERS)
        tail = _find_header(text, TAIL_HEADERS)

        def zone(start_h, *end_hs):
            if start_h is None:
                return ""
            s = start_h[1]
            ends = [h[0] for h in end_hs if h is not None and h[0] >= s]
            e = min(ends) if ends else len(text)
            return text[s:e]

        return {
            "duty": zone(duty, req, pref, tail),
            "req": zone(req, pref, tail),
            "pref": zone(pref, tail),
        }

    @staticmethod
    def _parse_duties(duty_zone: str) -> list[str]:
        """逐行解析编号职责，去掉编号前缀。"""
        out: list[str] = []
        for line in duty_zone.splitlines():
            line = _NUMBER_RE.sub("", line).strip().strip("：:")
            if line:
                out.append(line)
        return out

    def extract(self, record: JDRecord) -> ExtractionResult:
        text = record.text
        zones = self._zones(text)

        m = _TITLE_RE.search(text)
        title = m.group(1).strip() if m else record.job_title

        duties = self._parse_duties(zones["duty"])
        if zones["req"]:
            required = self.matcher.find_names(zones["req"])
        else:
            # 无版面结构的真实 JD（如 AutoWeakS 语料）没有"任职要求"段，
            # 兜底为全文扫描，避免技能字段整体漏抽
            required = self.matcher.find_names(text)
        preferred = self.matcher.find_names(zones["pref"]) if zones["pref"] else []
        # 加分技能不应重复出现在必备里（极少数版面混排的兜底）
        preferred = [s for s in preferred if s not in required]
        scenarios = self.matcher.find_scenarios(text)

        def snippet(zone_text: str, limit: int = 80) -> str:
            return " ".join(zone_text.split())[:limit]

        evidence = {
            "job_title": m.group(0) if m else "",
            "responsibilities": snippet(zones["duty"]),
            "required_skills": snippet(zones["req"]),
            "preferred_skills": snippet(zones["pref"]),
            "scenarios": "、".join(scenarios),
        }
        # 置信度：五个字段命中比例（离线规则全命中即 1.0）
        hits = sum([bool(title), bool(duties), bool(required), True, bool(scenarios)])
        confidence = round(hits / 5.0, 4)

        return ExtractionResult(
            jid=record.jid,
            job_title=title,
            responsibilities=duties,
            required_skills=required,
            preferred_skills=preferred,
            scenarios=scenarios,
            evidence=evidence,
            confidence=confidence,
            extractor=self.name,
            prompt_version="offline-v1",
        )