"""Agent 路由器 — 决策层（v3.0: 去掉独立 LLM，模糊场景 delegate 庞统）

路由模式：
  确定性路由：能力匹配、retry、handoff、assignee（纯 L1，不调 LLM）
  模糊路由：delegate 庞统（L3 spawn，通过 Gateway）

Router 只做决策，不做 spawn。返回 RouteDecision。
"""

from __future__ import annotations

import logging
import time
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Set

logger = logging.getLogger("moziplus-v2.router")


@dataclass
class RouteDecision:
    """路由决策结果"""
    agent_id: str
    reason: str
    mode: str  # "deterministic" | "agent_handoff" | "delegate" | "fallback"
    confidence: float = 1.0
    latency_ms: int = 0


@dataclass
class AgentProfile:
    """Agent 能力画像"""
    agent_id: str
    capabilities: List[str] = field(default_factory=list)
    can_review: bool = False
    max_concurrent: int = 1
    is_fallback: bool = False


# 已知 capability 白名单（司马懿 BUG-2：next_capability 校验）
KNOWN_CAPABILITIES = frozenset({
    "coding", "implementation", "scripting",
    "review", "quality_check", "debate",
    "deploy", "infrastructure", "docker", "vnpy",
    "risk", "compliance", "position_check",
    "data", "acquisition", "cleaning", "verification",
    "planning", "coordination", "escalation", "strategy",
})


class AgentRouter:
    """Agent 路由器 — 决策层

    v3.0: 去掉 LLMDriver（独立 OpenAI 客户端）。
    模糊场景不再调独立 LLM，改为 delegate 庞统（L3 spawn，走 Gateway）。
    """

    # 确定性 action type（不需要路由）
    LOCAL_ACTIONS = frozenset({
        "L1_guardrail", "format_check", "file_exists_check",
        "dependency_advance",
    })

    # 生命周期流转的状态-能力映射
    LIFECYCLE_CAPABILITY = {
        "review": {"capability": "review", "exclude_current": True},
        "failed": {"capability": "escalation", "exclude_current": False},
    }

    FALLBACK_AGENT = "pangtong-fujunshi"

    def __init__(
        self,
        agent_profiles: Optional[Dict[str, AgentProfile]] = None,
        counter: Optional[Any] = None,
    ):
        self.agent_profiles = agent_profiles or {}
        self.counter = counter
        # 构建 known capability 集合（从 profiles 中提取）
        self._known_capabilities: Set[str] = set()
        for prof in self.agent_profiles.values():
            self._known_capabilities.update(prof.capabilities)

    def route(self, task_info: Dict[str, Any],
              action_type: str = "") -> RouteDecision:
        """路由决策入口

        Args:
            task_info: 任务信息字典（需含 id, title, status, assignee,
                       current_agent, next_capability, task_type, description）
            action_type: 动作类型

        Returns:
            RouteDecision
        """
        start = time.monotonic()

        # ── 快速路径 1: 本地执行 ──
        if action_type in self.LOCAL_ACTIONS:
            return RouteDecision(
                agent_id="daemon",
                reason=f"Local action: {action_type}",
                mode="deterministic",
                latency_ms=int((time.monotonic() - start) * 1000),
            )

        # ── 快速路径 2: retry → 原执行者 ──
        if action_type == "retry":
            current = task_info.get("current_agent") or task_info.get("assignee")
            if current and current in self.agent_profiles:
                return RouteDecision(
                    agent_id=current,
                    reason="Retry original executor",
                    mode="deterministic",
                    latency_ms=int((time.monotonic() - start) * 1000),
                )

        # ── Mode B: Agent 声明式交接 ──
        next_cap = task_info.get("next_capability")
        if next_cap and self._validate_capability(next_cap):
            current = task_info.get("current_agent") or task_info.get("assignee")
            exclude = {current} if current else set()
            matched = self._match_capability(next_cap, exclude)
            if matched:
                return RouteDecision(
                    agent_id=matched,
                    reason=f"Agent handoff: needs {next_cap}",
                    mode="agent_handoff",
                    latency_ms=int((time.monotonic() - start) * 1000),
                )
            logger.info("next_capability '%s' no match, delegate to coordinator", next_cap)

        # ── 快速路径 3: 生命周期流转查表 ──
        lifecycle = self.LIFECYCLE_CAPABILITY.get(action_type)
        if not lifecycle:
            lifecycle = self.LIFECYCLE_CAPABILITY.get(task_info.get("status"))
        if lifecycle:
            cap = lifecycle["capability"]
            exclude_current = lifecycle.get("exclude_current", False)
            exclude = set()
            if exclude_current:
                current = task_info.get("current_agent") or task_info.get("assignee")
                if current:
                    exclude.add(current)
            matched = self._match_capability(cap, exclude)
            if matched:
                return RouteDecision(
                    agent_id=matched,
                    reason=f"Lifecycle: {action_type or task_info.get('status')} needs {cap}",
                    mode="deterministic",
                    latency_ms=int((time.monotonic() - start) * 1000),
                )

        # ── 快速路径 4: 有 assignee 且非生命周期流转 ──
        assignee = task_info.get("assignee")
        if assignee and assignee in self.agent_profiles and action_type not in ("review", "escalation"):
            return RouteDecision(
                agent_id=assignee,
                reason=f"Direct assignee: {assignee}",
                mode="deterministic",
                latency_ms=int((time.monotonic() - start) * 1000),
            )

        # ── 模糊场景: delegate 庞统（L3 spawn，走 Gateway）──
        return RouteDecision(
            agent_id=self.FALLBACK_AGENT,
            reason="Uncertain routing, delegate to coordinator",
            mode="delegate",
            confidence=0.0,
            latency_ms=int((time.monotonic() - start) * 1000),
        )

    def _validate_capability(self, capability: str) -> bool:
        """校验 next_capability 在已知集合内"""
        return capability in self._known_capabilities

    def _match_capability(self, capability: str,
                          exclude: Optional[Set[str]] = None) -> Optional[str]:
        """从能力画像中匹配 Agent"""
        candidates = []
        for aid, prof in self.agent_profiles.items():
            if aid in (exclude or set()):
                continue
            if capability in prof.capabilities:
                candidates.append(aid)

        if not candidates:
            return None
        if len(candidates) == 1:
            return candidates[0]
        # 多候选：选负载最低的
        if self.counter:
            return min(candidates,
                       key=lambda a: self.counter.active_agents.get(a, 0))
        return candidates[0]