"""
AWOOOI AIOps Phase 2 — Agent Orchestrator（排程指揮官）
======================================================
職責：序列化 5 個 Agent 的執行，管理 Redis Streams 審計軌跡，記錄 DB

執行順序：
    Diagnostician(snapshot)
        → Solver(diagnosis)
            → [Reviewer(plan) ‖ Critic(diagnosis, plan)]   # 並行
                → Coordinator(diagnosis, plan, verdict, critic)

設計原則：
1. 每個 Agent 已有內建 5s 熔斷（在各自的 run() 中）— Orchestrator 不重複
2. 全流程 30s 全局超時（GLOBAL_TIMEOUT_SEC）
3. Redis Streams XADD：best-effort，失敗不阻塞主流程
4. DB 記錄：每個 Agent turn 一行 agent_sessions（Immutable Event Sourcing）
5. AIOPS_P2_ENABLED=False 時禁止使用（呼叫方負責 gate）

Redis Stream key: aiops:p2:events
DB table: agent_sessions

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 asyncio
import dataclasses
import os
import time
import uuid
from datetime import UTC, datetime
from typing import TYPE_CHECKING

import structlog
from sqlalchemy import insert

from src.agents.coordinator_agent import get_coordinator_agent
from src.agents.critic_agent import compute_input_hash as critic_hash
from src.agents.critic_agent import get_critic_agent
from src.agents.diagnostician_agent import compute_input_hash as diag_hash
from src.agents.diagnostician_agent import get_diagnostician_agent
from src.agents.protocol import (
    ActionPlan,
    AgentRole,
    AgentSessionStatus,
    AgentVote,
    CriticReport,
    DecisionPackage,
    DiagnosisReport,
    ReviewVerdict,
)
from src.agents.reviewer_agent import compute_input_hash as reviewer_hash
from src.agents.reviewer_agent import get_reviewer_agent
from src.agents.solver_agent import compute_input_hash as solver_hash
from src.agents.solver_agent import get_solver_agent
from src.db.base import get_db_context
from src.db.models import AgentSession

if TYPE_CHECKING:
    from src.services.evidence_snapshot import EvidenceSnapshot

logger = structlog.get_logger(__name__)

def _agent_debate_global_timeout_seconds() -> float:
    """Return the full Phase 2 debate timeout.

    GCP Ollama incident analysis can legitimately take longer than the old
    90s guard. Keep a hard ceiling, but make it an explicit deployment knob.
    """

    raw = os.environ.get("AGENT_DEBATE_GLOBAL_TIMEOUT_SEC", "420.0")
    try:
        timeout = float(raw)
    except (TypeError, ValueError):
        timeout = 420.0
    return max(timeout, 90.0)


# 全局超時（所有 Agent 加起來）
# 2026-05-06 Codex: configurable for GCP-A/GCP-B/111 Ollama-first incident
# diagnosis. The old 90s guard was cutting off valid deep diagnosis runs.
GLOBAL_TIMEOUT_SEC = _agent_debate_global_timeout_seconds()

# 2026-04-16 ogt + Claude Sonnet 4.6: 移除 _PER_AGENT_TIMEOUT_SEC
# LLM 必須等到完整回應，不得人工截斷。降級只在真正異常（連線失敗、模型崩潰）觸發。
# 全流程由 GLOBAL_TIMEOUT_SEC 防掛死即可。

# Redis Stream key
STREAM_KEY = "aiops:p2:events"
STREAM_MAXLEN = 10_000  # 保留最近 10k 條事件


# ─────────────────────────────────────────────────────────────────────────────
# Public API
# ─────────────────────────────────────────────────────────────────────────────

async def run_agent_debate(
    snapshot: "EvidenceSnapshot",
    incident_id: str,
) -> DecisionPackage:
    """
    執行完整的 5 Agent 辯證流程。

    Args:
        snapshot: Phase 1 感官快照（EvidenceSnapshot）
        incident_id: 關聯 incident ID

    Returns:
        DecisionPackage（包含 recommended_action + confidence + requires_human_approval）

    Raises:
        不拋出 — 所有錯誤內部吸收，最壞情況返回 requires_human_approval=True 的 Package
    """
    session_id = str(uuid.uuid4())
    start_ms = int(time.monotonic() * 1000)

    logger.info(
        "agent_debate_start",
        session_id=session_id,
        incident_id=incident_id,
        snapshot_id=snapshot.snapshot_id,
    )

    try:
        package = await asyncio.wait_for(
            _debate(session_id, incident_id, snapshot),
            timeout=GLOBAL_TIMEOUT_SEC,
        )
        elapsed = int(time.monotonic() * 1000) - start_ms
        logger.info(
            "agent_debate_done",
            session_id=session_id,
            incident_id=incident_id,
            requires_human=package.requires_human_approval,
            confidence=package.confidence,
            status=package.session_status.value,
            elapsed_ms=elapsed,
        )

        # ADR-083 Phase 3: 辯證結果學習訊號接線（L7×D2）
        # best-effort — 學習失敗不阻塞主流程
        # 2026-04-15 ogt + Claude Sonnet 4.6（亞太）
        try:
            from src.services.learning_service import get_learning_service
            _critic_challenges = (
                package.critic_report.challenge_count
                if package.critic_report else 0
            )
            await get_learning_service().record_agent_session(
                session_id=session_id,
                incident_id=incident_id,
                final_confidence=package.confidence,
                requires_human_approval=package.requires_human_approval,
                all_agents_degraded=package.all_agents_degraded,
                critic_challenge_count=_critic_challenges,
            )
        except Exception as _lerr:
            logger.warning(
                "agent_session_learning_failed",
                session_id=session_id,
                error=str(_lerr),
            )

        return package

    except asyncio.TimeoutError:
        elapsed = int(time.monotonic() * 1000) - start_ms
        logger.error(
            "agent_debate_global_timeout",
            session_id=session_id,
            elapsed_ms=elapsed,
            timeout_sec=GLOBAL_TIMEOUT_SEC,
        )
        return _timeout_package(elapsed)

    except Exception:
        elapsed = int(time.monotonic() * 1000) - start_ms
        logger.exception("agent_debate_fatal", session_id=session_id)
        return _error_package(elapsed)


# ─────────────────────────────────────────────────────────────────────────────
# Internal — debate pipeline
# ─────────────────────────────────────────────────────────────────────────────

async def _debate(
    session_id: str,
    incident_id: str,
    snapshot: "EvidenceSnapshot",
) -> DecisionPackage:
    """實際的 Agent 辯證流程（在全局超時保護內執行）。"""

    # ── Step 1: Diagnostician ──────────────────────────────────────────────
    diagnostician = get_diagnostician_agent()
    diagnosis = await diagnostician.run(snapshot)
    await _record_turn(
        session_id=session_id,
        incident_id=incident_id,
        role=AgentRole.DIAGNOSTICIAN,
        input_hash=diag_hash(snapshot),
        output=diagnosis,
        latency_ms=diagnosis.latency_ms,
        vote=diagnosis.vote,
        degraded=diagnosis.degraded,
    )

    # ── Step 2: Solver ─────────────────────────────────────────────────────
    solver = get_solver_agent()
    # 2026-04-28: 把告警 labels 傳入，讓 Solver params 模板能填真實值
    _alert_labels = (snapshot.alert_info or {}).get("labels", {}) if snapshot.alert_info else {}
    plan = await solver.run(diagnosis, incident_labels=_alert_labels)
    await _record_turn(
        session_id=session_id,
        incident_id=incident_id,
        role=AgentRole.SOLVER,
        input_hash=solver_hash(diagnosis),
        output=plan,
        latency_ms=plan.latency_ms,
        vote=plan.vote,
        degraded=plan.degraded,
    )

    # ── Step 3: Reviewer ‖ Critic（並行）──────────────────────────────────
    reviewer = get_reviewer_agent()
    critic = get_critic_agent()

    verdict, critic_report = await asyncio.gather(
        reviewer.run(plan),
        critic.run(diagnosis, plan),
    )

    await asyncio.gather(
        _record_turn(
            session_id=session_id,
            incident_id=incident_id,
            role=AgentRole.REVIEWER,
            input_hash=reviewer_hash(plan),
            output=verdict,
            latency_ms=verdict.latency_ms,
            vote=verdict.vote,
            degraded=verdict.degraded,
        ),
        _record_turn(
            session_id=session_id,
            incident_id=incident_id,
            role=AgentRole.CRITIC,
            input_hash=critic_hash(diagnosis, plan),
            output=critic_report,
            latency_ms=critic_report.latency_ms,
            vote=critic_report.vote,
            degraded=critic_report.degraded,
        ),
        return_exceptions=True,  # MINOR-1: best-effort — 一個審計失敗不取消另一個
    )

    # ── Step 4: Coordinator ────────────────────────────────────────────────
    coordinator = get_coordinator_agent()
    package = await coordinator.run(diagnosis, plan, verdict, critic_report)
    await _record_turn(
        session_id=session_id,
        incident_id=incident_id,
        role=AgentRole.COORDINATOR,
        input_hash=_coordinator_input_hash(diagnosis, plan, verdict, critic_report),
        output=package,
        latency_ms=package.latency_ms,
        vote=AgentVote.APPROVE if not package.requires_human_approval else AgentVote.ABSTAIN,
        degraded=package.all_agents_degraded,
    )

    return package


# ─────────────────────────────────────────────────────────────────────────────
# Internal — DB + Redis recording
# ─────────────────────────────────────────────────────────────────────────────

async def _record_turn(
    session_id: str,
    incident_id: str,
    role: AgentRole,
    input_hash: str,
    output: object,
    latency_ms: int,
    vote: AgentVote,
    degraded: bool,
) -> None:
    """
    寫入 agent_sessions DB 行 + Redis Stream XADD（兩者皆 best-effort）。

    Immutable Event Sourcing — 只 INSERT，永不 UPDATE / DELETE。
    """
    output_json = _serialize_output(output)

    # ── DB 寫入 ──────────────────────────────────────────────────────────
    try:
        async with get_db_context() as db:
            await db.execute(
                insert(AgentSession).values(
                    id=str(uuid.uuid4()),
                    session_id=session_id,
                    incident_id=incident_id,
                    agent_role=role.value,
                    input_hash=input_hash,
                    output_json=output_json,
                    latency_ms=latency_ms,
                    vote=vote.value,
                    degraded=degraded,
                    created_at=datetime.now(UTC),
                )
            )
    except Exception:
        logger.exception(
            "agent_session_db_write_failed",
            session_id=session_id,
            role=role.value,
        )

    # ── Redis Stream XADD（best-effort，失敗靜默）────────────────────────
    try:
        from src.core.redis_client import get_redis
        redis = get_redis()
        await redis.xadd(
            STREAM_KEY,
            {
                "session_id": session_id,
                "incident_id": incident_id,
                "role": role.value,
                "vote": vote.value,
                "latency_ms": str(latency_ms),
                "degraded": "1" if degraded else "0",
            },
            maxlen=STREAM_MAXLEN,
            approximate=True,
        )
    except Exception:
        # Redis 失敗不阻塞主流程（觀測性非關鍵路徑）
        logger.warning(
            "agent_stream_xadd_failed",
            session_id=session_id,
            role=role.value,
        )


def _serialize_output(output: object) -> dict:
    """
    將 Agent 輸出 dataclass 轉為可 JSON 序列化的 dict。

    Gate 2: dataclasses.asdict() 保留 Enum 實例，json.dumps 會拋 TypeError。
    用 json.dumps(default=...) 先把 Enum 轉 .value 再 loads 回 dict。
    """
    import json
    from enum import Enum

    try:
        if dataclasses.is_dataclass(output) and not isinstance(output, type):
            raw = dataclasses.asdict(output)  # type: ignore[arg-type]
            return json.loads(
                json.dumps(raw, default=lambda o: o.value if isinstance(o, Enum) else str(o))
            )
        return {"raw": str(output)[:2000]}
    except Exception:
        return {"error": "serialization_failed"}


def _coordinator_input_hash(
    diagnosis: DiagnosisReport,
    plan: ActionPlan,
    verdict: ReviewVerdict,
    critic: CriticReport,
) -> str:
    """Coordinator 輸入 fingerprint（4 個 Agent 輸出的組合）。"""
    import hashlib
    key = (
        diagnosis.evidence_snapshot_id
        + (diagnosis.top_hypothesis.description if diagnosis.top_hypothesis else "")
        + (plan.top_candidate.action if plan.top_candidate else "")
        + verdict.vote.value
        + str(critic.challenge_count)
    )
    return hashlib.sha256(key.encode()).hexdigest()[:16]


# ─────────────────────────────────────────────────────────────────────────────
# Degraded fallback packages
# ─────────────────────────────────────────────────────────────────────────────

def _timeout_package(elapsed_ms: int) -> DecisionPackage:
    """全局超時 → 強制人工審核。"""
    return DecisionPackage(
        recommended_action=None,
        confidence=0.0,
        requires_human_approval=True,
        debate_summary=f"[超時] 辯證流程超過 {GLOBAL_TIMEOUT_SEC}s，強制升級人工審核",
        session_status=AgentSessionStatus.TIMEOUT,
        latency_ms=elapsed_ms,
        blocked_reason=f"全局超時 > {GLOBAL_TIMEOUT_SEC}s",
        all_agents_degraded=True,
    )


def _error_package(elapsed_ms: int) -> DecisionPackage:
    """未預期錯誤 → 強制人工審核。"""
    return DecisionPackage(
        recommended_action=None,
        confidence=0.0,
        requires_human_approval=True,
        debate_summary="[錯誤] 辯證流程發生未預期錯誤，強制升級人工審核",
        session_status=AgentSessionStatus.FAILED,
        latency_ms=elapsed_ms,
        blocked_reason="Orchestrator 未預期錯誤",
        all_agents_degraded=True,
    )