"""
Telegram Callback Dispatcher — 分類按鈕統一調度
================================================
Phase 5 Sprint 5.0-5.1 — 2026-04-14 Claude Sonnet 4.6
相關: docs/superpowers/plans/2026-04-14-PHASE-5-category-buttons-completion.md
       ADR-079 分類按鈕完整化

職責:
1. 從 callback_action_spec.yaml 載入 action registry
2. 接收 Telegram callback_data (action:incident_id or action:id:ts:rand)
3. 驗證 nonce（寫類按鈕）或 allow info（查類按鈕）
4. 依 spec 呼叫對應 MCP tool
5. Reply 執行結果到原告警卡片（reply_to_message_id）

設計原則:
- Registry pattern — 新增按鈕只需 yaml 一行，無需改 dispatcher code
- 模板變數: {incident_id} / {labels.xxx} / {signals[0].xxx} / {callback.user_id}
- 所有 action 都有 audit log（寫類額外 nonce 驗證 log）
- reply_to 原告警 message_id（從 Redis tg_msg:{incident_id}）

遵守「禁止 Mock 測試鐵律」: 純邏輯 + MCP dispatch，測試用真實 registry。
"""

from __future__ import annotations

import time
from dataclasses import dataclass
from functools import lru_cache
from pathlib import Path
from typing import Any

import structlog
import yaml

logger = structlog.get_logger(__name__)


# =============================================================================
# Data Types
# =============================================================================


@dataclass
class ActionSpec:
    """從 callback_action_spec.yaml 載入的單一 action 規格"""

    name: str
    label: str
    emoji: str
    risk: str  # low | medium | high | critical
    callback_format: str  # info | nonce
    category: str
    mcp_provider: str  # k8s | ssh | prometheus | signoz | database | internal
    mcp_tool: str
    mcp_params: dict[str, Any]
    reply_format: str  # text | code | url | truncated
    timeout_sec: int
    description: str
    requires_multi_sig: bool = False


@dataclass
class DispatchResult:
    """Dispatcher 執行結果"""

    success: bool
    action: str
    incident_id: str
    user_id: int | None
    result_text: str
    error: str | None = None
    duration_ms: float = 0.0


# =============================================================================
# Spec Registry
# =============================================================================


@lru_cache(maxsize=1)
def load_action_registry() -> dict[str, ActionSpec]:
    """
    載入 callback_action_spec.yaml 並快取（進程內不重載，重啟 Pod 才更新）

    Returns:
        {action_name: ActionSpec}
    """
    spec_path = Path(__file__).parent / "callback_action_spec.yaml"
    if not spec_path.exists():
        logger.warning("callback_action_spec_not_found", path=str(spec_path))
        return {}

    with spec_path.open("r", encoding="utf-8") as f:
        data = yaml.safe_load(f)

    registry: dict[str, ActionSpec] = {}
    for name, spec_dict in (data.get("actions") or {}).items():
        mcp = spec_dict.get("mcp", {}) or {}
        registry[name] = ActionSpec(
            name=name,
            label=spec_dict.get("label", name),
            emoji=spec_dict.get("emoji", ""),
            risk=spec_dict.get("risk", "medium"),
            callback_format=spec_dict.get("callback_format", "info"),
            category=spec_dict.get("category", ""),
            mcp_provider=mcp.get("provider", ""),
            mcp_tool=mcp.get("tool", ""),
            mcp_params=mcp.get("params") or {},
            reply_format=spec_dict.get("reply_format", "text"),
            timeout_sec=int(spec_dict.get("timeout_sec", 10)),
            description=spec_dict.get("description", ""),
            requires_multi_sig=bool(spec_dict.get("requires_multi_sig", False)),
        )
    logger.info("callback_action_registry_loaded", count=len(registry))
    return registry


def get_action_spec(action_name: str) -> ActionSpec | None:
    """查找單一 action 規格"""
    return load_action_registry().get(action_name)


def list_actions_for_category(alert_category: str) -> list[ActionSpec]:
    """列出特定分類的所有可用 action（供 _build_inline_keyboard 使用）"""
    return [
        spec for spec in load_action_registry().values()
        if spec.category == alert_category
    ]


# =============================================================================
# Template Variable Substitution
# =============================================================================


def _resolve_template(template: Any, context: dict) -> Any:
    """
    遞迴替換模板變數。

    支援:
    - {incident_id}
    - {labels.xxx} / {labels.xxx.yyy}
    - {signals[0].xxx}
    - {callback.user_id}

    Example:
        template = {"host": "{labels.instance}", "lines": 50}
        context = {"labels": {"instance": "192.168.0.110"}, "incident_id": "INC-123"}
        → {"host": "192.168.0.110", "lines": 50}
    """
    if isinstance(template, dict):
        return {k: _resolve_template(v, context) for k, v in template.items()}
    if isinstance(template, list):
        return [_resolve_template(v, context) for v in template]
    if isinstance(template, str) and "{" in template:
        # 找出所有 {xxx} placeholder 並替換
        import re
        def _repl(m: re.Match) -> str:
            key = m.group(1)
            val = _lookup_context(key, context)
            return str(val) if val is not None else m.group(0)
        return re.sub(r"\{([a-zA-Z0-9_.\[\]]+)\}", _repl, template)
    return template


def _lookup_context(key: str, context: dict) -> Any:
    """
    從 context 查表（支援巢狀 key: labels.instance / signals[0].alert_name）
    """
    parts = key.replace("[", ".").replace("]", "").split(".")
    cur: Any = context
    for part in parts:
        if part == "":
            continue
        if isinstance(cur, dict):
            cur = cur.get(part)
        elif isinstance(cur, list):
            try:
                cur = cur[int(part)]
            except (ValueError, IndexError):
                return None
        else:
            return None
        if cur is None:
            return None
    return cur


# =============================================================================
# Dispatcher (Sprint 5.1)
# =============================================================================


async def dispatch_action(
    action_name: str,
    incident_id: str,
    user_id: int | None = None,
    labels: dict | None = None,
    extra_context: dict | None = None,
) -> DispatchResult:
    """
    執行 callback action — 依 spec 呼叫 MCP tool

    Args:
        action_name: action 名稱（對應 spec registry）
        incident_id: 關聯 incident
        user_id: Telegram user id（callback 來源）
        labels: alert labels（供模板替換）
        extra_context: 額外上下文（signals 等）

    Returns:
        DispatchResult（包含 result_text 供 reply 使用）
    """
    start = time.perf_counter()
    spec = get_action_spec(action_name)
    if not spec:
        logger.warning("dispatch_action_unknown", action=action_name)
        return DispatchResult(
            success=False,
            action=action_name,
            incident_id=incident_id,
            user_id=user_id,
            result_text="",
            error=f"Unknown action: {action_name}",
            duration_ms=(time.perf_counter() - start) * 1000,
        )

    # 建立模板 context
    context = {
        "incident_id": incident_id,
        "labels": labels or {},
        "callback": {"user_id": user_id or 0},
        **(extra_context or {}),
    }
    resolved_params = _resolve_template(spec.mcp_params, context)

    # Audit log (all actions)
    logger.info(
        "dispatch_action_start",
        action=action_name,
        incident_id=incident_id,
        user_id=user_id,
        risk=spec.risk,
        provider=spec.mcp_provider,
        tool=spec.mcp_tool,
        params=resolved_params,
    )

    # MCP 呼叫（Sprint 5.1 只實作骨架，實際 MCP dispatch 在 Sprint 5.2/5.3）
    try:
        # Sprint 5.1 TODO: 接入 MCP registry
        # from src.plugins.mcp.registry import get_provider
        # provider = get_provider(spec.mcp_provider)
        # import asyncio
        # mcp_result = await asyncio.wait_for(
        #     provider.execute(spec.mcp_tool, resolved_params),
        #     timeout=spec.timeout_sec,
        # )
        # result_text = _format_reply(mcp_result, spec.reply_format, spec.label, spec.emoji)

        # Sprint 5.0 骨架：僅返回「尚未實作」提示
        result_text = (
            f"{spec.emoji} <b>{spec.label}</b>\n"
            f"⚠️ Phase 5 Sprint 5.2+ 實作中（spec 已載入：{spec.mcp_provider}/{spec.mcp_tool}）\n"
            f"參數: <code>{resolved_params}</code>"
        )
        duration = (time.perf_counter() - start) * 1000
        logger.info(
            "dispatch_action_stub",
            action=action_name,
            incident_id=incident_id,
            duration_ms=round(duration, 1),
        )
        return DispatchResult(
            success=True,
            action=action_name,
            incident_id=incident_id,
            user_id=user_id,
            result_text=result_text,
            duration_ms=duration,
        )
    except Exception as e:
        duration = (time.perf_counter() - start) * 1000
        logger.error(
            "dispatch_action_failed",
            action=action_name,
            incident_id=incident_id,
            error=str(e),
            duration_ms=round(duration, 1),
        )
        return DispatchResult(
            success=False,
            action=action_name,
            incident_id=incident_id,
            user_id=user_id,
            result_text=f"{spec.emoji} {spec.label} 執行失敗",
            error=str(e),
            duration_ms=duration,
        )


def _format_reply(
    mcp_result: Any, reply_format: str, label: str, emoji: str
) -> str:
    """
    依 spec 格式化 reply 文字。

    reply_format:
    - text: 單行文字
    - code: <code>...</code>
    - truncated: 截斷到 500 字
    - url: 直接返回 URL
    """
    header = f"{emoji} <b>{label}</b>"
    if reply_format == "url":
        return f"{header}\n{mcp_result}"
    if reply_format == "code":
        return f"{header}\n<code>{str(mcp_result)[:800]}</code>"
    if reply_format == "truncated":
        text = str(mcp_result)[:500]
        if len(str(mcp_result)) > 500:
            text += "...\n<i>(已截斷)</i>"
        return f"{header}\n<pre>{text}</pre>"
    return f"{header}\n{mcp_result}"