#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Auto-Repair Library v1.0
一键修复脚本库 — 根据诊断上下文自动匹配修复方案

用法:
  from auto_repair import match_repair, RepairAction

  ctx = {"status": "stopped", "source": "cli"}
  action = match_repair(ctx)
  if action:
      print(action.description)
      action.execute()  # 执行修复
"""

import subprocess
import logging
from typing import Optional, Dict, List
from dataclasses import dataclass, field

logger = logging.getLogger(__name__)

# ============================================================
# 修复动作定义
# ============================================================

@dataclass
class RepairAction:
    """一个可执行的修复动作"""
    issue: str                      # 问题标识
    description: str                # 人类可读描述
    risk: str                       # low / medium / high
    auto_approve: bool = False      # 是否可自动执行（无需用户确认）
    commands: List[str] = field(default_factory=list)  # PowerShell 命令列表

    def execute(self) -> bool:
        """执行修复命令，返回是否成功"""
        for cmd in self.commands:
            try:
                logger.info(f"执行修复: {self.issue} → {cmd}")
                result = subprocess.run(["powershell", "-Command", cmd],
                                       capture_output=True, text=True, timeout=30)
                if result.returncode != 0:
                    logger.warning(f"修复命令失败: {result.stderr[:100]}")
                    return False
            except Exception as e:
                logger.error(f"修复异常: {e}")
                return False
        logger.info(f"修复完成: {self.issue}")
        return True

    def summary(self) -> str:
        return f"[{self.risk}] {self.description}"


# ============================================================
# 修复方案库
# ============================================================

REPAIR_PLANS: List[Dict] = [
    # ---- Gateway 停止 ----
    {
        "match": {"status": "stopped"},
        "actions": [
            RepairAction(
                issue="gateway_stopped",
                description="Gateway 进程未运行，尝试重启",
                risk="low",
                auto_approve=False,
                commands=["openclaw gateway restart"]
            ),
        ]
    },

    # ---- RPC 连接失败 ----
    {
        "match": {"rpc_ok": False},
        "actions": [
            RepairAction(
                issue="rpc_failed",
                description="Gateway RPC 连接异常，尝试重启",
                risk="medium",
                auto_approve=False,
                commands=["openclaw gateway restart"]
            ),
        ]
    },

    # ---- CLI 检查失败 ----
    {
        "match": {"source": "cli", "status": "cli_error"},
        "actions": [
            RepairAction(
                issue="cli_unavailable",
                description="openclaw CLI 不可用，检查安装路径",
                risk="low",
                auto_approve=True,
                commands=[
                    "Get-Command openclaw -ErrorAction SilentlyContinue | Select-Object Source"
                ]
            ),
        ]
    },

    # ---- HTTP API 不可达（Gateway 未响应）----
    {
        "match": {"source": "http", "status": "unreachable"},
        "actions": [
            RepairAction(
                issue="gateway_unreachable",
                description="Gateway HTTP API 不可达，检查端口并尝试重启",
                risk="medium",
                auto_approve=False,
                commands=[
                    "Test-NetConnection -ComputerName 127.0.0.1 -Port 18788 -WarningAction SilentlyContinue | Select-Object TcpTestSucceeded",
                    "openclaw gateway restart"
                ]
            ),
        ]
    },

    # ---- 配置错误 ----
    {
        "match": {"source": "sim", "status": "healthy"},
        "actions": []  # 模拟健康检查，无修复必要
    },
]

# ============================================================
# 匹配引擎
# ============================================================

def match_repair(ctx: Dict[str, any]) -> Optional[List[RepairAction]]:
    """
    根据诊断上下文匹配修复方案。
    返回匹配的 RepairAction 列表，无匹配则返回 None。
    """
    if not ctx:
        return None

    best_score = 0
    best_actions = None

    for plan in REPAIR_PLANS:
        match = plan["match"]
        score = 0
        total = len(match)

        for key, expected in match.items():
            actual = ctx.get(key)
            if actual == expected:
                score += 1
            elif isinstance(expected, (list, tuple)) and actual in expected:
                score += 1
            elif actual and str(expected).lower() in str(actual).lower():
                score += 0.5

        # 匹配度：至少有一半字段匹配
        if total > 0 and score / total >= 0.5 and score > best_score:
            best_score = score
            best_actions = plan["actions"]

    return best_actions if best_actions else None


def format_repair_suggestion(actions: List[RepairAction]) -> str:
    """将修复方案格式化为可读文本"""
    if not actions:
        return "未找到匹配的自动修复方案，需要人工诊断。"

    lines = ["**🔧 自动修复方案**\n"]
    for action in actions:
        risk_emoji = {"low": "✅", "medium": "⚠️", "high": "🔴"}.get(action.risk, "❓")
        auto = "可自动执行" if action.auto_approve else "需要确认"
        lines.append(f"- {risk_emoji} **{action.description}** ({auto})")
    lines.append(f"\n共有 {len(actions)} 个修复步骤")
    return "\n".join(lines)


# ============================================================
# 快速测试
# ============================================================

if __name__ == "__main__":
    # 测试样例
    test_cases = [
        {"status": "stopped", "source": "cli"},
        {"rpc_ok": False, "source": "cli"},
        {"status": "unreachable", "source": "http"},
        {"status": "running", "rpc_ok": True, "source": "cli"},
    ]

    for ctx in test_cases:
        actions = match_repair(ctx)
        print(f"\n诊断上下文: {ctx}")
        print(f"匹配结果: {format_repair_suggestion(actions) if actions else '无匹配'}")