"""
AWOOOI AIOps Phase 2 — Critic Agent（質疑者）
=============================================
職責：刻意唱反調，防止幻覺與 echo chamber

輸入：DiagnosisReport + ActionPlan（兩者都看）
輸出：CriticReport（challenges[] 列表 + overall_assessment）

設計原則：
1. Critic 的工作是找漏洞，不是說好話（防 sycophancy）
2. prompt 強制要求批判性思維：「如果診斷是錯的，還有哪 3 種可能？」
3. challenge_count > 0 是 Phase 2 退出條件之一
4. Critic 連續 3 次找到 Diagnostician 嚴重漏洞 → 觸發 Diagnostician 狀態不穩（Phase 4 實作）
5. 熔斷降級：LLM 失敗 → 輸出空 challenges（不阻塞 Coordinator）
6. Critic 和 Reviewer 並行執行（都不阻塞對方）

ADR-082: Phase 2 多 Agent 協作
2026-04-15 ogt + Claude Sonnet 4.6（亞太）: Phase 2 初始建立
"""

from __future__ import annotations

import hashlib
import time
from typing import Any

import structlog

from src.agents.base import BaseAgent
from src.agents.protocol import (
    ActionPlan,
    AgentRole,
    AgentVote,
    Challenge,
    CriticReport,
    DiagnosisReport,
)
from src.services.sanitization_service import sanitize

logger = structlog.get_logger(__name__)

# Critic 挑戰數量上限（防止 LLM 生成無限質疑）
MAX_CHALLENGES = 5


class CriticAgent(BaseAgent):
    """
    Critic Agent — 系統性懷疑論者

    Usage:
        agent = CriticAgent()
        report = await agent.run(diagnosis, plan)
    """

    AGENT_NAME = AgentRole.CRITIC.value
    AGENT_DESCRIPTION = (
        "Devil's advocate. Challenges diagnosis and proposed actions to prevent "
        "hallucination and echo chamber effects."
    )

    async def run(
        self,
        diagnosis: DiagnosisReport,
        plan: ActionPlan,
        timeout_sec: float = 0.0,  # noqa: ARG002 — 已廢棄，保留簽名相容性
    ) -> CriticReport:
        """
        批判性審查診斷和方案。

        Args:
            diagnosis: Diagnostician 輸出
            plan: Solver 輸出
            timeout_sec: 已廢棄 (2026-04-16 ogt) — LLM 等完整回應，真實異常才降級

        Returns:
            CriticReport（真實異常時 degraded=True）
        """
        start_ms = int(time.monotonic() * 1000)

        try:
            report = await self._critique(diagnosis, plan)
            report.latency_ms = int(time.monotonic() * 1000) - start_ms
            logger.info(
                "critic_done",
                challenges=report.challenge_count,
                has_critical=report.has_critical_challenge,
                vote=report.vote,
                latency_ms=report.latency_ms,
            )
            return report

        except Exception:
            latency = int(time.monotonic() * 1000) - start_ms
            logger.exception("critic_error")
            return self._degraded_report(latency, "error")

    async def _critique(
        self,
        diagnosis: DiagnosisReport,
        plan: ActionPlan,
    ) -> CriticReport:
        """LLM 批判性推理。"""
        top_hypothesis = diagnosis.top_hypothesis
        top_candidate = plan.top_candidate

        prompt = self._build_prompt({
            "hypothesis": top_hypothesis.description if top_hypothesis else "（無假設）",
            "action": top_candidate.action if top_candidate else "（無方案）",
            "confidence": top_hypothesis.confidence if top_hypothesis else 0.0,
        })

        from src.services.openclaw import get_openclaw
        openclaw = get_openclaw()
        response_text, _provider, success = await openclaw.call(prompt)

        if not success or not response_text:
            return self._degraded_report(0, "llm_failed")

        parsed = self._parse_response(sanitize(response_text, "critic_output"))
        challenges = _extract_challenges(parsed)

        # 有 critical challenge → vote = REJECT
        vote = AgentVote.REJECT if any(c.severity == "critical" for c in challenges) else AgentVote.APPROVE

        return CriticReport(
            challenges=challenges,
            overall_assessment=str(parsed.get("overall_assessment", ""))[:1000],
            latency_ms=0,
            vote=vote,
        )

    def _build_prompt(self, context: dict[str, Any]) -> str:
        return f"""你是 AWOOOI SRE 系統的質疑者 Agent（Critic）。

你的工作是：找出診斷和方案的弱點。不是說好話，是找漏洞。

當前診斷：{context.get("hypothesis", "")}
當前方案：{context.get("action", "")}
診斷信心：{context.get("confidence", 0.0):.0%}

必須回答以下問題（每個問題產出一個 challenge）：
1. 如果這個診斷是錯的，還有哪些可能的根因？
2. 這個方案有什麼副作用或風險？
3. 是否有更好的替代方案被忽略了？

每個 challenge 標記嚴重度：
- "minor"：小瑕疵，不影響執行
- "major"：值得 Coordinator 考慮，但不是阻擋條件
- "critical"：嚴重邏輯漏洞，必須阻止此方案執行

以 JSON 回覆：
{{
  "challenges": [
    {{
      "target": "diagnosis",
      "argument": "可能是 OOM 但也可能是 code bug，需要看 GC logs 確認",
      "severity": "major"
    }}
  ],
  "overall_assessment": "診斷可信但方案風險偏高"
}}"""

    def _parse_response(self, response: str) -> dict[str, Any]:
        return self._extract_json(response)

    def analyze(self, context: dict[str, Any]) -> Any:
        raise NotImplementedError("Use run() for Phase 2 agents")

    def _degraded_report(
        self,
        latency_ms: int,
        reason: str = "unknown",
    ) -> CriticReport:
        """熔斷降級：輸出空 challenges（不阻塞 Coordinator）"""
        return CriticReport(
            challenges=[],
            overall_assessment=f"[降級] Critic LLM 失敗（{reason}），跳過批判性審查",
            latency_ms=latency_ms,
            vote=AgentVote.ABSTAIN,
            degraded=True,
        )


# ─────────────────────────────────────────────────────────────────────────────
# Helpers
# ─────────────────────────────────────────────────────────────────────────────

def _extract_challenges(parsed: dict[str, Any]) -> list[Challenge]:
    """從 LLM 解析結果提取 challenges（按嚴重度排序）。"""
    raw = parsed.get("challenges", [])
    challenges = []
    severity_order = {"critical": 0, "major": 1, "minor": 2}

    for item in raw:
        if not isinstance(item, dict):
            continue
        c = Challenge(
            target=str(item.get("target", "unknown"))[:50],
            argument=str(item.get("argument", ""))[:500],
            severity=item.get("severity", "minor") if item.get("severity") in severity_order else "minor",
        )
        challenges.append(c)

    challenges.sort(key=lambda c: severity_order.get(c.severity, 2))
    return challenges[:MAX_CHALLENGES]


def compute_input_hash(diagnosis: DiagnosisReport, plan: ActionPlan) -> str:
    key = diagnosis.evidence_snapshot_id + (
        diagnosis.top_hypothesis.description if diagnosis.top_hypothesis else ""
    ) + (
        plan.top_candidate.action if plan.top_candidate else ""
    )
    return hashlib.sha256(key.encode()).hexdigest()[:16]


# ─────────────────────────────────────────────────────────────────────────────
# Singleton
# ─────────────────────────────────────────────────────────────────────────────

_agent: CriticAgent | None = None


def get_critic_agent() -> CriticAgent:
    global _agent
    if _agent is None:
        _agent = CriticAgent()
    return _agent