"""AI 分析报告路由（/api/ai-analysis）

提供：
- 报告列表
- 报告详情
- 手动触发分析（12小时频率限制）
- 重新生成报告
- 检查某日是否有报告
"""

import json
from datetime import datetime, timezone, timedelta

from fastapi import APIRouter, HTTPException
from fastapi.responses import JSONResponse

from database import get_connection, dict_from_row

_CST = timezone(timedelta(hours=8))
_NO_CACHE_HEADERS = {"Cache-Control": "no-store, no-cache, must-revalidate, max-age=0"}

router = APIRouter()


def _has_ai_report(trade_date: str) -> bool:
    conn = get_connection()
    try:
        row = conn.execute(
            "SELECT 1 FROM ai_reports WHERE trade_date = ? AND report_type = 'daily' LIMIT 1",
            (trade_date,)
        ).fetchone()
        return row is not None
    finally:
        conn.close()


def _can_trigger(trade_date: str) -> tuple[bool, str]:
    """检查是否可以触发分析（同一交易日内可随时重新生成）"""
    return True, ""


@router.get("/ai-analysis/latest", summary="最新 AI 分析报告")
async def get_latest_report():
    conn = get_connection()
    try:
        # issue_number：按报告日期序数作为总期号
        row = conn.execute(
            """SELECT r.*,
                      (SELECT COUNT(*) FROM ai_reports WHERE trade_date <= r.trade_date) AS issue_number
               FROM ai_reports r ORDER BY r.trade_date DESC, r.id DESC LIMIT 1"""
        ).fetchone()
        if not row:
            raise HTTPException(status_code=404, detail="暂无分析报告")
        item = dict_from_row(row)
        item["toolsUsed"] = json.loads(item.pop("tools_used") or "[]")
        return JSONResponse({"data": item}, headers=_NO_CACHE_HEADERS)
    finally:
        conn.close()


@router.get("/ai-analysis", summary="AI 分析报告列表")
async def list_reports():
    conn = get_connection()
    try:
        rows = conn.execute(
            "SELECT id, trade_date, report_type, title, summary, tools_used, model, tokens_used, "
            "generation_count, created_at, updated_at "
            "FROM ai_reports ORDER BY trade_date DESC, id DESC LIMIT 50"
        ).fetchall()
        items = []
        for r in rows:
            item = dict_from_row(r)
            item["toolsUsed"] = json.loads(item.pop("tools_used") or "[]")
            items.append(item)
        return JSONResponse({"data": items}, headers=_NO_CACHE_HEADERS)
    finally:
        conn.close()


@router.get("/ai-analysis/{report_id}", summary="AI 分析报告详情")
async def get_report(report_id: int):
    conn = get_connection()
    try:
        row = conn.execute("SELECT * FROM ai_reports WHERE id = ?", (report_id,)).fetchone()
        if not row:
            raise HTTPException(status_code=404, detail="报告不存在")
        item = dict_from_row(row)
        item["toolsUsed"] = json.loads(item.pop("tools_used") or "[]")
        return JSONResponse({"data": item}, headers=_NO_CACHE_HEADERS)
    finally:
        conn.close()


@router.get("/ai-analysis/check/{trade_date}", summary="检查某日是否有 AI 分析报告")
async def check_report(trade_date: str):
    has = _has_ai_report(trade_date)
    return JSONResponse({"data": {"hasReport": has, "tradeDate": trade_date}})


@router.post("/ai-analysis/{report_id}/regenerate", summary="重新生成 AI 分析报告")
async def regenerate_report(report_id: int):
    conn = get_connection()
    try:
        row = conn.execute("SELECT trade_date FROM ai_reports WHERE id = ?", (report_id,)).fetchone()
        if not row:
            raise HTTPException(status_code=404, detail="报告不存在")
        trade_date = row["trade_date"]
    finally:
        conn.close()

    from services.ai_service import collect_ai_analysis
    result = await collect_ai_analysis(trade_date)
    return JSONResponse({"data": result})