"""
Webhook API Schema - 告警接收 Pydantic 模型
=============================================

從 api/v1/webhooks.py 抽取至 models 層 (ADR-024 四層架構)

設計原則:
- AlertPayload: 外部告警接收格式 (Prometheus, K8s, Alertmanager 等)
- AlertResponse: 告警處理回應格式
- 不含業務邏輯，純資料結構

版本: v1.0
建立: 2026-04-01 (台北時區)
建立者: Claude Code (R4 Router 瘦身 #129)
"""

from typing import Literal

from pydantic import BaseModel, Field


class AlertPayload(BaseModel):
    """
    外部告警 Payload

    接收來自 Prometheus AlertManager、K8s Event Watcher、Grafana 等
    外部監控系統的告警通知。

    OpenClaw AI 會自動分析告警並建立待簽核卡片。

    Example:
        ```json
        {
            "alert_type": "k8s_pod_crash",
            "severity": "critical",
            "source": "prometheus",
            "target_resource": "harbor-core-7d4b8c9f5-xk2m3",
            "namespace": "harbor",
            "message": "Pod CrashLoopBackOff detected",
            "metrics": {"restart_count": 5, "cpu_percent": 95}
        }
        ```
    """

    alert_type: Literal[
        "k8s_node_failure",      # K8s 節點故障
        "k8s_pod_crash",         # Pod 崩潰
        "db_connection_timeout", # 資料庫連線超時
        "service_404",           # 服務 404 錯誤
        "high_cpu",              # CPU 飆高
        "high_memory",           # 記憶體飆高
        "disk_full",             # 磁碟滿
        "ssl_expiry",            # SSL 憑證即將過期
        "custom",                # 自訂告警
    ] = Field(..., description="告警類型")

    severity: Literal["info", "warning", "critical"] = Field(
        "warning",
        description="告警嚴重度",
    )

    source: str = Field(
        ...,
        description="告警來源 (例如: prometheus, k8s-event-watcher)",
    )

    target_resource: str = Field(
        ...,
        description="受影響的資源 (例如: harbor, nginx-ingress-7d4b8c9f5-xk2m3)",
    )

    namespace: str = Field(
        "default",
        description="K8s Namespace",
    )

    message: str = Field(
        ...,
        description="告警訊息",
    )

    metrics: dict | None = Field(
        None,
        description="相關指標數據 (例如: {cpu_percent: 95, memory_percent: 80})",
    )

    labels: dict | None = Field(
        None,
        description="告警標籤 (例如: {app: harbor, team: devops})",
    )


class AlertResponse(BaseModel):
    """
    告警處理回應

    包含 OpenClaw AI 分析結果：
    - 風險等級 (risk_level)
    - 爆炸半徑 (透過 approval_id 查詢)
    - 建議修復腳本 (suggested_action)

    戰略 B 新增：
    - hit_count: 告警聚合次數
    - converged: 是否為收斂的重複告警
    """

    success: bool = Field(..., description="處理是否成功")
    message: str = Field(..., description="處理結果訊息")
    alert_id: str | None = Field(None, description="告警唯一識別碼")
    approval_created: bool = Field(False, description="是否已建立待簽核卡片")
    approval_id: str | None = Field(None, description="待簽核卡片 ID (UUID)")
    risk_level: str | None = Field(None, description="AI 判定風險等級 (low/medium/high/critical)")
    suggested_action: str | None = Field(None, description="AI 建議修復腳本")
    # 戰略 B: 告警風暴收斂
    hit_count: int = Field(1, description="告警聚合次數 (相同指紋觸發次數)")
    converged: bool = Field(False, description="是否為收斂的重複告警 (跳過 LLM)")