# -*- coding: utf-8 -*-
"""
阿里云 DashScope（通义千问）提取面板结构化数据
从新闻文本中提取战损、报复指数、基地状态等，供 db_merge 落库
API Key 通过环境变量 DASHSCOPE_API_KEY 配置
"""
import json
import os
import re
from datetime import datetime, timezone
from typing import Any, Dict, Optional

from panel_schema import validate_category, validate_severity, validate_summary


EXTRACT_TEXT_MAX_LEN = int(os.environ.get("EXTRACT_TEXT_MAX_LEN", "4000"))


def _call_dashscope_extract(text: str, timeout: int = 15) -> Optional[Dict[str, Any]]:
    """调用阿里云 DashScope 从新闻全文中提取精确结构化数据，仅填写报道明确给出的数字与事实。"""
    api_key = os.environ.get("DASHSCOPE_API_KEY", "").strip()
    if not api_key or not text or len(str(text).strip()) < 10:
        return None
    try:
        import dashscope
        from http import HTTPStatus

        dashscope.api_key = api_key
        raw = str(text).strip()[:EXTRACT_TEXT_MAX_LEN]

        prompt = f"""从以下美伊/中东新闻**全文或摘要**中，提取**报道明确给出的数字与事实**，输出 JSON。规则：
1. 仅填写报道中**直接出现、可核对**的数据，不要推测或估算。
2. 无明确依据的字段**必须省略**，不要填 0 或猜。
3. **战损一律按增量**：只填本则报道中「本次/此次/今日」**新增**数量。报道若只给「累计总数」「迄今共」**不要填**该字段。
4. **攻击地点**：提取双方遭袭地点。美军/盟军基地被打击 → side=us；伊朗/亲伊设施被打击 → side=iran。name_keywords 用「中文|英文」，可填多处。

字段：
- summary: 1-2 句中文事实概括，≤80 字
- category: deployment|alert|intel|diplomatic|other
- severity: low|medium|high|critical
- 战损（**仅填本则报道的新增增量**）: us_personnel_killed, iran_personnel_killed, us_personnel_wounded, iran_personnel_wounded, us_civilian_killed, iran_civilian_killed, us_civilian_wounded, iran_civilian_wounded, us_bases_destroyed, iran_bases_destroyed, us_bases_damaged, iran_bases_damaged, us_aircraft, iran_aircraft, us_warships, iran_warships, us_armor, iran_armor, us_vehicles, iran_vehicles, us_drones, iran_drones, us_missiles, iran_missiles, us_helicopters, iran_helicopters, us_submarines, iran_submarines, us_carriers, iran_carriers, us_civilian_ships, iran_civilian_ships, us_airport_port, iran_airport_port
- retaliation_sentiment: 0-100（仅当报道涉及伊朗报复情绪时）
- wall_street_value: 0-100（仅当报道涉及美股/市场时）
- key_location_updates: **双方攻击地点**。每项 {{"name_keywords":"阿萨德|asad","side":"us或iran（被打击方）","status":"attacked","damage_level":1-3}}。美军基地：阿萨德|asad、乌代德|udeid、埃尔比勒|erbil、因吉尔利克|incirlik。伊朗：德黑兰|tehran、布什尔|bushehr、伊斯法罕|isfahan、阿巴斯|abbas、纳坦兹|natanz

原文：
{raw}

直接输出 JSON，不要其他解释："""

        response = dashscope.Generation.call(
            model="qwen-turbo",
            messages=[{"role": "user", "content": prompt}],
            result_format="message",
            max_tokens=512,
        )

        if response.status_code != HTTPStatus.OK:
            return None
        raw = (response.output.get("choices", [{}])[0].get("message", {}).get("content", "") or "").strip()
        raw = re.sub(r"^```\w*\s*|\s*```$", "", raw)
        return json.loads(raw)
    except Exception:
        return None


def extract_from_news(text: str, timestamp: Optional[str] = None) -> Dict[str, Any]:
    """
    从新闻文本提取结构化数据，符合面板 schema
    返回: { situation_update?, combat_losses_delta?, retaliation?, wall_street?, key_location_updates? }
    """
    ts = timestamp or datetime.now(timezone.utc).strftime("%Y-%m-%dT%H:%M:%S.000Z")
    out: Dict[str, Any] = {}
    parsed = _call_dashscope_extract(text)
    if not parsed:
        return out

    if parsed.get("summary"):
        out["situation_update"] = {
            "summary": validate_summary(str(parsed["summary"])[:120], 120),
            "category": validate_category(str(parsed.get("category", "other")).lower()),
            "severity": validate_severity(str(parsed.get("severity", "medium")).lower()),
            "timestamp": ts,
        }

    loss_us = {}
    loss_ir = {}
    for k in ["personnel_killed", "personnel_wounded", "civilian_killed", "civilian_wounded",
              "bases_destroyed", "bases_damaged", "aircraft", "warships", "armor", "vehicles",
              "drones", "missiles", "helicopters", "submarines", "carriers", "civilian_ships", "airport_port"]:
        uk, ik = f"us_{k}", f"iran_{k}"
        if uk in parsed and isinstance(parsed[uk], (int, float)):
            loss_us[k] = max(0, int(parsed[uk]))
        if ik in parsed and isinstance(parsed[ik], (int, float)):
            loss_ir[k] = max(0, int(parsed[ik]))
    if loss_us or loss_ir:
        out["combat_losses_delta"] = {}
        if loss_us:
            out["combat_losses_delta"]["us"] = loss_us
        if loss_ir:
            out["combat_losses_delta"]["iran"] = loss_ir

    if "retaliation_sentiment" in parsed:
        v = parsed["retaliation_sentiment"]
        if isinstance(v, (int, float)) and 0 <= v <= 100:
            out["retaliation"] = {"value": int(v), "time": ts}

    if "wall_street_value" in parsed:
        v = parsed["wall_street_value"]
        if isinstance(v, (int, float)) and 0 <= v <= 100:
            out["wall_street"] = {"time": ts, "value": int(v)}

    if "key_location_updates" in parsed and isinstance(parsed["key_location_updates"], list):
        valid = []
        for u in parsed["key_location_updates"]:
            if isinstance(u, dict) and u.get("name_keywords") and u.get("side") in ("us", "iran"):
                valid.append({
                    "name_keywords": str(u["name_keywords"]),
                    "side": u["side"],
                    "status": str(u.get("status", "attacked"))[:20],
                    "damage_level": min(3, max(1, int(u["damage_level"]))) if isinstance(u.get("damage_level"), (int, float)) else 2,
                })
        if valid:
            out["key_location_updates"] = valid

    return out