"""AI 监控后台聚合服务层。

提供 Dashboard 总览、调度任务管理、调用记录查询、缓存失效、
Token 预算、批量执行（含成本二次确认）、告警管理等功能。

所有数据库操作使用 psycopg2 同步连接，方法签名为 async（FastAPI 兼容）。
查询强制 site_id 隔离（当 site_id 参数不为 None 时）。
"""

from __future__ import annotations

import asyncio
import logging
import uuid
from datetime import datetime, timezone, timedelta

from app.ai.budget_tracker import BudgetTracker
from app.database import get_connection

logger = logging.getLogger(__name__)

# 批量执行预估：每次调用平均 Token 消耗
AVG_TOKENS_PER_CALL = 2000

# 批量执行内存存储 TTL（秒）
_BATCH_TTL_SECONDS = 600  # 10 分钟


class AdminAIService:
    """AI 监控后台聚合服务。"""

    def __init__(self, budget_tracker: BudgetTracker | None = None) -> None:
        self._budget = budget_tracker
        self._batch_store: dict[str, dict] = {}  # batch_id → {params, expires_at}

    # ── Dashboard ─────────────────────────────────────────

    async def get_dashboard(self, site_id: int | None = None) -> dict:
        """聚合所有 Dashboard 数据。"""
        today_stats = await self._get_today_stats(site_id)
        trend_7d = await self._get_7d_trend(site_id)
        app_dist = await self._get_app_distribution(site_id)
        app_health = await self._get_app_health(site_id)
        budget = await self.get_budget()
        recent_alerts = await self._get_recent_alerts(site_id)
        return {
            **today_stats,
            "trend_7d": trend_7d,
            "app_distribution": app_dist,
            "budget": budget,
            "recent_alerts": recent_alerts,
            "app_health": app_health,
        }

    async def _get_today_stats(self, site_id: int | None) -> dict:
        """今日调用次数、成功率、Token 消耗、平均延迟。"""
        site_clause, params = _site_filter(site_id)
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    f"""
                    SELECT
                        COUNT(*)                                          AS total_calls,
                        COUNT(*) FILTER (WHERE status = 'success')        AS success_count,
                        COALESCE(SUM(tokens_used), 0)                     AS total_tokens,
                        COALESCE(AVG(latency_ms) FILTER (WHERE latency_ms IS NOT NULL), 0)
                                                                          AS avg_latency
                    FROM biz.ai_run_logs
                    WHERE created_at >= CURRENT_DATE
                      AND created_at <  CURRENT_DATE + INTERVAL '1 day'
                      {site_clause}
                    """,
                    params,
                )
                row = cur.fetchone()
            conn.commit()
        finally:
            conn.close()

        total, success, tokens, avg_lat = row if row else (0, 0, 0, 0)
        rate = round(success / total, 4) if total > 0 else 0.0
        return {
            "today_calls": total,
            "today_success_rate": rate,
            "today_tokens": int(tokens),
            "today_avg_latency_ms": round(float(avg_lat), 2),
        }

    async def _get_7d_trend(self, site_id: int | None) -> list[dict]:
        """近 7 天按日聚合。"""
        site_clause, params = _site_filter(site_id)
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    f"""
                    SELECT
                        created_at::date                                  AS day,
                        COUNT(*)                                          AS calls,
                        COUNT(*) FILTER (WHERE status = 'success')        AS success_count
                    FROM biz.ai_run_logs
                    WHERE created_at >= CURRENT_DATE - INTERVAL '6 days'
                      {site_clause}
                    GROUP BY day
                    ORDER BY day
                    """,
                    params,
                )
                rows = cur.fetchall()
            conn.commit()
        finally:
            conn.close()

        return [
            {
                "date": row[0].isoformat(),
                "calls": row[1],
                "success_rate": round(row[2] / row[1], 4) if row[1] > 0 else 0.0,
            }
            for row in rows
        ]

    async def _get_app_distribution(self, site_id: int | None) -> list[dict]:
        """各 App 调用占比。"""
        site_clause, params = _site_filter(site_id)
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    f"""
                    SELECT app_type, COUNT(*) AS cnt
                    FROM biz.ai_run_logs
                    WHERE created_at >= CURRENT_DATE - INTERVAL '6 days'
                      {site_clause}
                    GROUP BY app_type
                    ORDER BY cnt DESC
                    """,
                    params,
                )
                rows = cur.fetchall()
            conn.commit()
        finally:
            conn.close()

        total = sum(r[1] for r in rows) or 1
        return [
            {
                "app_type": row[0],
                "count": row[1],
                "percentage": round(row[1] / total, 4),
            }
            for row in rows
        ]

    async def _get_app_health(self, site_id: int | None) -> list[dict]:
        """各 App 最近一次调用状态。"""
        site_clause, params = _site_filter(site_id)
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    f"""
                    SELECT DISTINCT ON (app_type)
                        app_type,
                        status       AS last_status,
                        created_at   AS last_call_at
                    FROM biz.ai_run_logs
                    WHERE TRUE {site_clause}
                    ORDER BY app_type, created_at DESC
                    """,
                    params,
                )
                rows = cur.fetchall()
            conn.commit()
        finally:
            conn.close()

        return [
            {
                "app_type": row[0],
                "last_status": row[1],
                "last_call_at": row[2].isoformat() if row[2] else None,
            }
            for row in rows
        ]

    async def _get_recent_alerts(self, site_id: int | None, limit: int = 10) -> list[dict]:
        """最近告警事件（Dashboard 用）。"""
        site_clause, params = _site_filter(site_id)
        params = (*params, limit)
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    f"""
                    SELECT id, app_type, status, alert_status,
                           error_message, created_at
                    FROM biz.ai_run_logs
                    WHERE status IN ('failed', 'timeout', 'circuit_open')
                      {site_clause}
                    ORDER BY created_at DESC
                    LIMIT %s
                    """,
                    params,
                )
                cols = [d[0] for d in cur.description]
                rows = cur.fetchall()
            conn.commit()
        finally:
            conn.close()

        return [_row_to_dict(cols, r) for r in rows]

    # ── 调度任务 ──────────────────────────────────────────

    async def list_trigger_jobs(
        self, filters: dict, page: int = 1, page_size: int = 20,
    ) -> dict:
        """分页查询 ai_trigger_jobs + 今日去重统计。"""
        where_parts: list[str] = []
        params: list = []

        for key in ("event_type", "status", "site_id"):
            if filters.get(key) is not None:
                where_parts.append(f"{key} = %s")
                params.append(filters[key])

        if filters.get("date_from"):
            where_parts.append("created_at >= %s")
            params.append(filters["date_from"])
        if filters.get("date_to"):
            where_parts.append("created_at <= %s")
            params.append(filters["date_to"])

        where_sql = ("WHERE " + " AND ".join(where_parts)) if where_parts else ""
        offset = (page - 1) * page_size

        conn = get_connection()
        try:
            with conn.cursor() as cur:
                # 总数
                cur.execute(
                    f"SELECT COUNT(*) FROM biz.ai_trigger_jobs {where_sql}",
                    params,
                )
                total = cur.fetchone()[0]

                # 分页数据
                cur.execute(
                    f"""
                    SELECT id, event_type, member_id, status, app_chain,
                           is_forced, site_id, started_at, finished_at, created_at
                    FROM biz.ai_trigger_jobs
                    {where_sql}
                    ORDER BY created_at DESC
                    LIMIT %s OFFSET %s
                    """,
                    (*params, page_size, offset),
                )
                cols = [d[0] for d in cur.description]
                rows = cur.fetchall()

                # 今日去重跳过数
                cur.execute(
                    """
                    SELECT COUNT(*)
                    FROM biz.ai_trigger_jobs
                    WHERE status = 'skipped_duplicate'
                      AND created_at >= CURRENT_DATE
                      AND created_at <  CURRENT_DATE + INTERVAL '1 day'
                    """,
                )
                today_skipped = cur.fetchone()[0]
            conn.commit()
        finally:
            conn.close()

        return {
            "items": [_row_to_dict(cols, r) for r in rows],
            "total": total,
            "page": page,
            "page_size": page_size,
            "today_skipped_duplicates": today_skipped,
        }

    async def get_trigger_job(self, job_id: int) -> dict | None:
        """单条调度任务详情。"""
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    """
                    SELECT id, event_type, member_id, status, app_chain,
                           is_forced, site_id, started_at, finished_at,
                           created_at, payload, error_message, connector_type
                    FROM biz.ai_trigger_jobs
                    WHERE id = %s
                    """,
                    (job_id,),
                )
                cols = [d[0] for d in cur.description]
                row = cur.fetchone()
            conn.commit()
        finally:
            conn.close()

        if row is None:
            return None
        return _row_to_dict(cols, row)

    async def retry_trigger_job(self, job_id: int) -> int:
        """创建新 trigger_job（is_forced=true），返回新 job_id。"""
        original = await self.get_trigger_job(job_id)
        if original is None:
            raise ValueError(f"trigger_job {job_id} 不存在")

        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    """
                    INSERT INTO biz.ai_trigger_jobs
                        (event_type, member_id, site_id, connector_type,
                         payload, app_chain, is_forced, status)
                    VALUES (%s, %s, %s, %s, %s, %s, true, 'pending')
                    RETURNING id
                    """,
                    (
                        original["event_type"],
                        original.get("member_id"),
                        original["site_id"],
                        original.get("connector_type", "feiqiu"),
                        original.get("payload"),
                        original.get("app_chain"),
                    ),
                )
                new_id = cur.fetchone()[0]
            conn.commit()
        except Exception:
            conn.rollback()
            raise
        finally:
            conn.close()

        return new_id

    # ── 调用记录 ──────────────────────────────────────────

    async def list_run_logs(
        self, filters: dict, page: int = 1, page_size: int = 20,
    ) -> dict:
        """分页查询 ai_run_logs。"""
        where_parts: list[str] = []
        params: list = []

        for key in ("app_type", "status", "trigger_type", "site_id"):
            if filters.get(key) is not None:
                where_parts.append(f"{key} = %s")
                params.append(filters[key])

        if filters.get("date_from"):
            where_parts.append("created_at >= %s")
            params.append(filters["date_from"])
        if filters.get("date_to"):
            where_parts.append("created_at <= %s")
            params.append(filters["date_to"])

        where_sql = ("WHERE " + " AND ".join(where_parts)) if where_parts else ""
        offset = (page - 1) * page_size

        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    f"SELECT COUNT(*) FROM biz.ai_run_logs {where_sql}",
                    params,
                )
                total = cur.fetchone()[0]

                cur.execute(
                    f"""
                    SELECT id, app_type, trigger_type, member_id,
                           tokens_used, latency_ms, status, site_id, created_at
                    FROM biz.ai_run_logs
                    {where_sql}
                    ORDER BY created_at DESC
                    LIMIT %s OFFSET %s
                    """,
                    (*params, page_size, offset),
                )
                cols = [d[0] for d in cur.description]
                rows = cur.fetchall()
            conn.commit()
        finally:
            conn.close()

        return {
            "items": [_row_to_dict(cols, r) for r in rows],
            "total": total,
            "page": page,
            "page_size": page_size,
        }

    async def get_run_log(self, log_id: int) -> dict | None:
        """单条调用记录详情（含完整 prompt/response，不脱敏）。"""
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    """
                    SELECT id, app_type, trigger_type, member_id,
                           tokens_used, latency_ms, status, site_id,
                           created_at, request_prompt, response_text,
                           error_message, session_id, finished_at
                    FROM biz.ai_run_logs
                    WHERE id = %s
                    """,
                    (log_id,),
                )
                cols = [d[0] for d in cur.description]
                row = cur.fetchone()
            conn.commit()
        finally:
            conn.close()

        if row is None:
            return None
        return _row_to_dict(cols, row)

    # ── 缓存管理 ──────────────────────────────────────────

    async def invalidate_cache(
        self, site_id: int, app_type: str | None = None, member_id: int | None = None,
    ) -> int:
        """批量缓存失效，返回受影响记录数。"""
        where_parts = ["site_id = %s"]
        params: list = [site_id]

        if app_type is not None:
            where_parts.append("cache_type = %s")
            params.append(app_type)
        if member_id is not None:
            where_parts.append("target_id = %s")
            params.append(str(member_id))

        where_sql = " AND ".join(where_parts)

        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    f"""
                    UPDATE biz.ai_cache
                    SET status = 'invalidated'
                    WHERE {where_sql}
                      AND status != 'invalidated'
                    """,
                    params,
                )
                affected = cur.rowcount
            conn.commit()
        except Exception:
            conn.rollback()
            raise
        finally:
            conn.close()

        return affected

    # ── Token 预算 ────────────────────────────────────────

    async def get_budget(self) -> dict:
        """Token 预算使用情况。"""
        if self._budget is not None:
            status = self._budget.check_budget()
            daily_limit = self._budget.daily_limit
            monthly_limit = self._budget.monthly_limit
            return {
                "daily_used": status.daily_used,
                "daily_limit": daily_limit,
                "daily_pct": round(status.daily_used / daily_limit, 4) if daily_limit > 0 else 0.0,
                "monthly_used": status.monthly_used,
                "monthly_limit": monthly_limit,
                "monthly_pct": round(status.monthly_used / monthly_limit, 4) if monthly_limit > 0 else 0.0,
            }

        # 无 BudgetTracker 时直接查询
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    """
                    SELECT
                        COALESCE(SUM(tokens_used) FILTER (
                            WHERE created_at >= CURRENT_DATE
                              AND created_at <  CURRENT_DATE + INTERVAL '1 day'
                        ), 0) AS daily_used,
                        COALESCE(SUM(tokens_used) FILTER (
                            WHERE created_at >= date_trunc('month', CURRENT_DATE)
                              AND created_at <  date_trunc('month', CURRENT_DATE) + INTERVAL '1 month'
                        ), 0) AS monthly_used
                    FROM biz.ai_run_logs
                    WHERE status = 'success'
                    """,
                )
                row = cur.fetchone()
            conn.commit()
        finally:
            conn.close()

        daily_used, monthly_used = (int(row[0]), int(row[1])) if row else (0, 0)
        daily_limit = 100_000
        monthly_limit = 2_000_000
        return {
            "daily_used": daily_used,
            "daily_limit": daily_limit,
            "daily_pct": round(daily_used / daily_limit, 4) if daily_limit > 0 else 0.0,
            "monthly_used": monthly_used,
            "monthly_limit": monthly_limit,
            "monthly_pct": round(monthly_used / monthly_limit, 4) if monthly_limit > 0 else 0.0,
        }

    # ── 批量执行 ──────────────────────────────────────────

    async def estimate_batch(
        self, app_types: list[str], member_ids: list[int], site_id: int,
    ) -> dict:
        """生成 batch_id，存入内存（TTL 10min），返回预估。"""
        self._cleanup_expired_batches()

        batch_id = uuid.uuid4().hex
        estimated_calls = len(app_types) * len(member_ids)
        estimated_tokens = estimated_calls * AVG_TOKENS_PER_CALL

        self._batch_store[batch_id] = {
            "params": {
                "app_types": app_types,
                "member_ids": member_ids,
                "site_id": site_id,
            },
            "expires_at": datetime.now(timezone.utc) + timedelta(seconds=_BATCH_TTL_SECONDS),
        }

        return {
            "batch_id": batch_id,
            "estimated_calls": estimated_calls,
            "estimated_tokens": estimated_tokens,
        }

    async def confirm_batch(self, batch_id: str) -> None:
        """取出参数，异步执行批量调用。"""
        self._cleanup_expired_batches()

        entry = self._batch_store.pop(batch_id, None)
        if entry is None:
            raise ValueError(f"batch_id 无效或已过期: {batch_id}")

        params = entry["params"]
        logger.info(
            "批量执行确认: batch_id=%s apps=%s members=%d site_id=%s",
            batch_id,
            params["app_types"],
            len(params["member_ids"]),
            params["site_id"],
        )
        # 后台异步执行（具体调用链由路由层注入 dispatcher 处理）
        asyncio.create_task(
            self._run_batch(params["app_types"], params["member_ids"], params["site_id"])
        )

    async def _run_batch(
        self, app_types: list[str], member_ids: list[int], site_id: int,
    ) -> None:
        """后台批量执行（占位实现，实际由 dispatcher 驱动）。"""
        logger.info(
            "批量执行开始: apps=%s members=%d site_id=%s",
            app_types, len(member_ids), site_id,
        )
        # 实际执行逻辑在路由层通过 dispatcher.handle_trigger 驱动
        # 此处仅记录日志，避免服务层直接依赖 dispatcher 实例

    def _cleanup_expired_batches(self) -> None:
        """清理过期 batch。"""
        now = datetime.now(timezone.utc)
        expired = [
            bid for bid, entry in self._batch_store.items()
            if entry["expires_at"] <= now
        ]
        for bid in expired:
            del self._batch_store[bid]
        if expired:
            logger.debug("清理过期 batch: %d 个", len(expired))

    # ── 告警管理 ──────────────────────────────────────────

    async def list_alerts(
        self,
        alert_status: str | None = None,
        site_id: int | None = None,
        page: int = 1,
        page_size: int = 20,
    ) -> dict:
        """告警列表：ai_run_logs WHERE status IN ('failed','timeout','circuit_open')。"""
        where_parts = ["status IN ('failed', 'timeout', 'circuit_open')"]
        params: list = []

        if alert_status is not None:
            if alert_status == "pending":
                # pending 包含 NULL 和 'pending'
                where_parts.append("(alert_status IS NULL OR alert_status = 'pending')")
            else:
                where_parts.append("alert_status = %s")
                params.append(alert_status)

        if site_id is not None:
            where_parts.append("site_id = %s")
            params.append(site_id)

        where_sql = "WHERE " + " AND ".join(where_parts)
        offset = (page - 1) * page_size

        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    f"SELECT COUNT(*) FROM biz.ai_run_logs {where_sql}",
                    params,
                )
                total = cur.fetchone()[0]

                cur.execute(
                    f"""
                    SELECT id, app_type, status, alert_status,
                           error_message, created_at
                    FROM biz.ai_run_logs
                    {where_sql}
                    ORDER BY created_at DESC
                    LIMIT %s OFFSET %s
                    """,
                    (*params, page_size, offset),
                )
                cols = [d[0] for d in cur.description]
                rows = cur.fetchall()
            conn.commit()
        finally:
            conn.close()

        return {
            "items": [_row_to_dict(cols, r) for r in rows],
            "total": total,
            "page": page,
            "page_size": page_size,
        }

    async def ack_alert(self, log_id: int) -> str:
        """确认告警：alert_status → acknowledged。"""
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    """
                    UPDATE biz.ai_run_logs
                    SET alert_status = 'acknowledged'
                    WHERE id = %s
                      AND status IN ('failed', 'timeout', 'circuit_open')
                    """,
                    (log_id,),
                )
            conn.commit()
        except Exception:
            conn.rollback()
            raise
        finally:
            conn.close()

        return "acknowledged"

    async def ignore_alert(self, log_id: int) -> str:
        """忽略告警：alert_status → ignored。"""
        conn = get_connection()
        try:
            with conn.cursor() as cur:
                cur.execute(
                    """
                    UPDATE biz.ai_run_logs
                    SET alert_status = 'ignored'
                    WHERE id = %s
                      AND status IN ('failed', 'timeout', 'circuit_open')
                    """,
                    (log_id,),
                )
            conn.commit()
        except Exception:
            conn.rollback()
            raise
        finally:
            conn.close()

        return "ignored"


# ── 工具函数 ──────────────────────────────────────────────


def _site_filter(site_id: int | None) -> tuple[str, tuple]:
    """生成 site_id 过滤子句和参数。"""
    if site_id is None:
        return "", ()
    return "AND site_id = %s", (site_id,)


def _row_to_dict(columns: list[str], row: tuple) -> dict:
    """将数据库行转换为 dict，处理 datetime 序列化。"""
    result = {}
    for col, val in zip(columns, row):
        if isinstance(val, datetime):
            result[col] = val.isoformat()
        else:
            result[col] = val
    return result