"""
监控告警工具 — 实时异常检测与熔断
"""

import logging
from typing import Any, Dict, List, Optional

from agent.tools import tool
from agent.tools.models import ToolResult

logger = logging.getLogger(__name__)


@tool(description="检查投放指标是否异常（成本突增/转化骤降/预算超支/CTR异常）")
async def monitor_check_metrics(
    account_id: int,
    check_items: List[str],
    threshold: Optional[Dict[str, float]] = None,
    time_window: str = "1h",
) -> ToolResult:
    """检查各项投放指标是否触发异常阈值。

    Args:
        account_id: 广告主账号ID
        check_items: 检查项列表，可选：
            - cost_spike: 成本突增（小时CPA > 目标CPA × 阈值）
            - cvr_drop: 转化率骤降（小时CVR < 昨日同时段 × 阈值）
            - budget_overrun: 预算超支（日消耗 > 日预算 × 阈值）
            - ctr_anomaly: CTR异常低（CTR < 历史均值 × 阈值）
            - balance_low: 账户余额不足（余额 < N天预估消耗）
        threshold: 阈值配置，如 {"cost_spike_ratio": 2.0, "cvr_drop_ratio": 0.5}
        time_window: 检查时间窗口 "1h"（最近1小时）/ "3h" / "today"（今日）

    Returns:
        异常检测结果，包含触发的异常项和详细信息
    """
    from examples.auto_put_ad.tools.data_query import data_query
    from examples.auto_put_ad.tools.ad_api import account_get_info

    default_threshold = {
        "cost_spike_ratio": 2.0,      # CPA 超过目标 2 倍
        "cvr_drop_ratio": 0.5,         # CVR 低于昨日 50%
        "budget_overrun_ratio": 0.95,  # 消耗达到预算 95%
        "ctr_low_ratio": 0.5,          # CTR 低于均值 50%
        "balance_days": 3,             # 余额不足 3 天消耗
    }
    thresholds = {**default_threshold, **(threshold or {})}

    anomalies = []

    # 1. 成本突增检查
    if "cost_spike" in check_items:
        # 查询最近1小时的CPA
        result = await data_query(
            query_type="cost_trend",
            date_range={"start_date": "today", "end_date": "today"},
            dimensions=["hour"],
            metrics=["cpa"],
            filters={"account_id": account_id},
        )
        # 实际实现需要对比目标CPA
        # 这里简化为占位逻辑
        anomalies.append({
            "type": "cost_spike",
            "severity": "warning",
            "message": "（占位）成本突增检测需要实现目标CPA对比逻辑"
        })

    # 2. 转化率骤降检查
    if "cvr_drop" in check_items:
        anomalies.append({
            "type": "cvr_drop",
            "severity": "info",
            "message": "（占位）CVR骤降检测需要实现同比逻辑"
        })

    # 3. 预算超支检查
    if "budget_overrun" in check_items:
        result = await data_query(
            query_type="account_summary",
            date_range={"start_date": "today", "end_date": "today"},
            metrics=["cost"],
            filters={"account_id": account_id},
        )
        # 需要对比日预算
        anomalies.append({
            "type": "budget_overrun",
            "severity": "info",
            "message": "（占位）预算超支检测需要获取日预算配置"
        })

    # 4. CTR异常检查
    if "ctr_anomaly" in check_items:
        anomalies.append({
            "type": "ctr_anomaly",
            "severity": "info",
            "message": "（占位）CTR异常检测需要历史均值数据"
        })

    # 5. 余额不足检查
    if "balance_low" in check_items:
        result = await account_get_info(account_id=account_id)
        if "失败" not in result.title:
            balance = (result.metadata or {}).get("balance", 0)
            # 需要预估日消耗
            anomalies.append({
                "type": "balance_low",
                "severity": "info",
                "message": f"账户余额: {balance/100:.2f}元（需实现日消耗预估）"
            })

    # 汇总结果
    if not anomalies:
        return ToolResult(title="监控检查通过", output=f"所有检查项正常（{', '.join(check_items)}）")

    critical = [a for a in anomalies if a.get("severity") == "critical"]
    warnings = [a for a in anomalies if a.get("severity") == "warning"]

    lines = [f"检测到 {len(anomalies)} 项异常："]
    for a in anomalies:
        icon = "🔴" if a["severity"] == "critical" else "⚠️" if a["severity"] == "warning" else "ℹ️"
        lines.append(f"{icon} [{a['type']}] {a['message']}")

    return ToolResult(
        title=f"监控检查完成（{len(critical)}个严重，{len(warnings)}个警告）",
        output="\n".join(lines),
        metadata={"anomalies": anomalies, "thresholds": thresholds},
    )


@tool(description="执行熔断操作：批量暂停异常广告")
async def monitor_circuit_break(
    account_id: int,
    target_ids: List[int],
    reason: str,
) -> ToolResult:
    """批量暂停异常广告，记录熔断原因（3.0 只有广告层级）。

    Args:
        account_id: 广告主账号ID
        target_ids: 需要熔断的广告ID列表（adgroup_id）
        reason: 熔断原因（记录到日志）
    """
    from examples.auto_put_ad.tools.ad_api import ad_batch_update_status

    logger.warning(
        "[熔断] 账户 %s 触发熔断，暂停 %d 个广告，原因: %s",
        account_id, len(target_ids), reason
    )

    result = await ad_batch_update_status(
        adgroup_ids=target_ids,
        configured_status="AD_STATUS_SUSPEND",
        account_id=account_id,
    )

    if "失败" in result.title:
        return ToolResult(
            title="熔断执行失败",
            output=f"暂停广告失败: {result.output}\n原因: {reason}"
        )

    return ToolResult(
        title=f"熔断执行完成（暂停{len(target_ids)}个广告）",
        output=f"已暂停广告: {target_ids}\n熔断原因: {reason}\n\n{result.output}",
        metadata={"target_ids": target_ids, "reason": reason},
    )