"""
Clarification mechanism for intent recognition.
[AC-CLARIFY] 澄清机制实现

核心功能：
1. 统一置信度计算
2. 硬拦截规则（confidence检查、required_slots检查）
3. 澄清状态管理
4. 埋点指标收集
"""

import logging
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Any
import uuid

logger = logging.getLogger(__name__)


T_HIGH = 0.75
T_LOW = 0.45
MAX_CLARIFY_RETRY = 3


class ClarifyReason(str, Enum):
    INTENT_AMBIGUITY = "intent_ambiguity"
    MISSING_SLOT = "missing_slot"
    LOW_CONFIDENCE = "low_confidence"
    MULTI_INTENT = "multi_intent"


class ClarifyMetrics:
    _instance = None
    
    def __new__(cls):
        if cls._instance is None:
            cls._instance = super().__new__(cls)
            cls._instance._clarify_trigger_count = 0
            cls._instance._clarify_converge_count = 0
            cls._instance._misroute_count = 0
        return cls._instance
    
    def record_clarify_trigger(self) -> None:
        self._clarify_trigger_count += 1
        logger.debug(f"[AC-CLARIFY-METRICS] clarify_trigger_count: {self._clarify_trigger_count}")
    
    def record_clarify_converge(self) -> None:
        self._clarify_converge_count += 1
        logger.debug(f"[AC-CLARIFY-METRICS] clarify_converge_count: {self._clarify_converge_count}")
    
    def record_misroute(self) -> None:
        self._misroute_count += 1
        logger.debug(f"[AC-CLARIFY-METRICS] misroute_count: {self._misroute_count}")
    
    def get_metrics(self) -> dict[str, int]:
        return {
            "clarify_trigger_rate": self._clarify_trigger_count,
            "clarify_converge_rate": self._clarify_converge_count,
            "misroute_rate": self._misroute_count,
        }
    
    def get_rates(self, total_requests: int) -> dict[str, float]:
        if total_requests == 0:
            return {
                "clarify_trigger_rate": 0.0,
                "clarify_converge_rate": 0.0,
                "misroute_rate": 0.0,
            }
        
        return {
            "clarify_trigger_rate": self._clarify_trigger_count / total_requests,
            "clarify_converge_rate": self._clarify_converge_count / total_requests if self._clarify_trigger_count > 0 else 0.0,
            "misroute_rate": self._misroute_count / total_requests,
        }
    
    def reset(self) -> None:
        self._clarify_trigger_count = 0
        self._clarify_converge_count = 0
        self._misroute_count = 0


def get_clarify_metrics() -> ClarifyMetrics:
    return ClarifyMetrics()


@dataclass
class IntentCandidate:
    intent_id: str
    intent_name: str
    confidence: float
    response_type: str | None = None
    target_kb_ids: list[str] | None = None
    flow_id: str | None = None
    fixed_reply: str | None = None
    transfer_message: str | None = None
    
    def to_dict(self) -> dict[str, Any]:
        return {
            "intent_id": self.intent_id,
            "intent_name": self.intent_name,
            "confidence": self.confidence,
            "response_type": self.response_type,
            "target_kb_ids": self.target_kb_ids,
            "flow_id": self.flow_id,
            "fixed_reply": self.fixed_reply,
            "transfer_message": self.transfer_message,
        }


@dataclass
class HybridIntentResult:
    intent: IntentCandidate | None
    confidence: float
    candidates: list[IntentCandidate] = field(default_factory=list)
    need_clarify: bool = False
    clarify_reason: ClarifyReason | None = None
    missing_slots: list[str] = field(default_factory=list)
    
    def to_dict(self) -> dict[str, Any]:
        return {
            "intent": self.intent.to_dict() if self.intent else None,
            "confidence": self.confidence,
            "candidates": [c.to_dict() for c in self.candidates],
            "need_clarify": self.need_clarify,
            "clarify_reason": self.clarify_reason.value if self.clarify_reason else None,
            "missing_slots": self.missing_slots,
        }
    
    @classmethod
    def from_fusion_result(cls, fusion_result: Any) -> "HybridIntentResult":
        candidates = []
        if fusion_result.clarify_candidates:
            for c in fusion_result.clarify_candidates:
                candidates.append(IntentCandidate(
                    intent_id=str(c.id),
                    intent_name=c.name,
                    confidence=0.0,
                    response_type=getattr(c, "response_type", None),
                    target_kb_ids=getattr(c, "target_kb_ids", None),
                    flow_id=str(c.flow_id) if getattr(c, "flow_id", None) else None,
                    fixed_reply=getattr(c, "fixed_reply", None),
                    transfer_message=getattr(c, "transfer_message", None),
                ))
        
        if fusion_result.final_intent:
            final_candidate = IntentCandidate(
                intent_id=str(fusion_result.final_intent.id),
                intent_name=fusion_result.final_intent.name,
                confidence=fusion_result.final_confidence,
                response_type=fusion_result.final_intent.response_type,
                target_kb_ids=fusion_result.final_intent.target_kb_ids,
                flow_id=str(fusion_result.final_intent.flow_id) if fusion_result.final_intent.flow_id else None,
                fixed_reply=fusion_result.final_intent.fixed_reply,
                transfer_message=fusion_result.final_intent.transfer_message,
            )
            if not any(c.intent_id == final_candidate.intent_id for c in candidates):
                candidates.insert(0, final_candidate)
        
        clarify_reason = None
        if fusion_result.need_clarify:
            if fusion_result.decision_reason == "multi_intent":
                clarify_reason = ClarifyReason.MULTI_INTENT
            elif fusion_result.decision_reason == "gray_zone":
                clarify_reason = ClarifyReason.INTENT_AMBIGUITY
            else:
                clarify_reason = ClarifyReason.LOW_CONFIDENCE
        
        return cls(
            intent=candidates[0] if candidates else None,
            confidence=fusion_result.final_confidence,
            candidates=candidates,
            need_clarify=fusion_result.need_clarify,
            clarify_reason=clarify_reason,
        )


@dataclass
class ClarifyState:
    reason: ClarifyReason
    asked_slot: str | None = None
    retry_count: int = 0
    candidates: list[IntentCandidate] = field(default_factory=list)
    asked_intent_ids: list[str] = field(default_factory=list)
    created_at: float = field(default_factory=time.time)
    
    def to_dict(self) -> dict[str, Any]:
        return {
            "reason": self.reason.value,
            "asked_slot": self.asked_slot,
            "retry_count": self.retry_count,
            "candidates": [c.to_dict() for c in self.candidates],
            "asked_intent_ids": self.asked_intent_ids,
            "created_at": self.created_at,
        }
    
    def increment_retry(self) -> "ClarifyState":
        self.retry_count += 1
        return self
    
    def is_max_retry(self) -> bool:
        return self.retry_count >= MAX_CLARIFY_RETRY


class ClarificationEngine:
    
    def __init__(
        self,
        t_high: float = T_HIGH,
        t_low: float = T_LOW,
        max_retry: int = MAX_CLARIFY_RETRY,
    ):
        self._t_high = t_high
        self._t_low = t_low
        self._max_retry = max_retry
        self._metrics = get_clarify_metrics()
    
    def compute_confidence(
        self,
        rule_score: float = 0.0,
        semantic_score: float = 0.0,
        llm_score: float = 0.0,
        w_rule: float = 0.5,
        w_semantic: float = 0.3,
        w_llm: float = 0.2,
    ) -> float:
        total_weight = w_rule + w_semantic + w_llm
        if total_weight == 0:
            return 0.0
        
        weighted_score = (
            rule_score * w_rule +
            semantic_score * w_semantic +
            llm_score * w_llm
        )
        
        return min(1.0, max(0.0, weighted_score / total_weight))
    
    def check_hard_block(
        self,
        result: HybridIntentResult,
        required_slots: list[str] | None = None,
        filled_slots: dict[str, Any] | None = None,
    ) -> tuple[bool, ClarifyReason | None]:
        if result.confidence < self._t_high:
            return True, ClarifyReason.LOW_CONFIDENCE
        
        if required_slots and filled_slots is not None:
            missing = [s for s in required_slots if s not in filled_slots]
            if missing:
                return True, ClarifyReason.MISSING_SLOT
        
        return False, None
    
    def should_trigger_clarify(
        self,
        result: HybridIntentResult,
        required_slots: list[str] | None = None,
        filled_slots: dict[str, Any] | None = None,
    ) -> tuple[bool, ClarifyState | None]:
        if result.confidence >= self._t_high:
            if required_slots and filled_slots is not None:
                missing = [s for s in required_slots if s not in filled_slots]
                if missing:
                    self._metrics.record_clarify_trigger()
                    return True, ClarifyState(
                        reason=ClarifyReason.MISSING_SLOT,
                        asked_slot=missing[0],
                        candidates=result.candidates,
                    )
            return False, None
        
        if result.confidence < self._t_low:
            self._metrics.record_clarify_trigger()
            return True, ClarifyState(
                reason=ClarifyReason.LOW_CONFIDENCE,
                candidates=result.candidates,
            )
        
        self._metrics.record_clarify_trigger()
        
        reason = result.clarify_reason or ClarifyReason.INTENT_AMBIGUITY
        return True, ClarifyState(
            reason=reason,
            candidates=result.candidates,
        )
    
    def generate_clarify_prompt(
        self,
        state: ClarifyState,
        slot_label: str | None = None,
    ) -> str:
        if state.reason == ClarifyReason.MISSING_SLOT:
            slot_name = slot_label or state.asked_slot or "相关信息"
            return f"为了更好地为您服务，请告诉我您的{slot_name}。"
        
        if state.reason == ClarifyReason.LOW_CONFIDENCE:
            return "抱歉，我不太理解您的意思，能否请您详细描述一下您的需求？"
        
        if state.reason == ClarifyReason.MULTI_INTENT and len(state.candidates) > 1:
            candidates = state.candidates[:3]
            if len(candidates) == 2:
                return (
                    f"请问您是想「{candidates[0].intent_name}」"
                    f"还是「{candidates[1].intent_name}」？"
                )
            else:
                options = "、".join([f"「{c.intent_name}」" for c in candidates[:-1]])
                return f"请问您是想{options}，还是「{candidates[-1].intent_name}」？"
        
        if state.reason == ClarifyReason.INTENT_AMBIGUITY and len(state.candidates) > 1:
            candidates = state.candidates[:2]
            return (
                f"请问您是想「{candidates[0].intent_name}」"
                f"还是「{candidates[1].intent_name}」？"
            )
        
        return "请问您具体想了解什么？"
    
    def process_clarify_response(
        self,
        user_message: str,
        state: ClarifyState,
        intent_router: Any = None,
        rules: list[Any] | None = None,
    ) -> HybridIntentResult:
        state.increment_retry()
        
        if state.is_max_retry():
            self._metrics.record_misroute()
            return HybridIntentResult(
                intent=None,
                confidence=0.0,
                need_clarify=False,
            )
        
        if state.reason == ClarifyReason.MISSING_SLOT:
            self._metrics.record_clarify_converge()
            return HybridIntentResult(
                intent=state.candidates[0] if state.candidates else None,
                confidence=0.8,
                candidates=state.candidates,
                need_clarify=False,
            )
        
        return HybridIntentResult(
            intent=None,
            confidence=0.0,
            candidates=state.candidates,
            need_clarify=True,
            clarify_reason=state.reason,
        )
    
    def get_metrics(self) -> dict[str, int]:
        return self._metrics.get_metrics()
    
    def get_rates(self, total_requests: int) -> dict[str, float]:
        return self._metrics.get_rates(total_requests)


class ClarifySessionManager:
    _sessions: dict[str, ClarifyState] = {}
    
    @classmethod
    def get_session(cls, session_id: str) -> ClarifyState | None:
        return cls._sessions.get(session_id)
    
    @classmethod
    def set_session(cls, session_id: str, state: ClarifyState) -> None:
        cls._sessions[session_id] = state
        logger.debug(f"[AC-CLARIFY] Session state set: session={session_id}, reason={state.reason}")
    
    @classmethod
    def clear_session(cls, session_id: str) -> None:
        if session_id in cls._sessions:
            del cls._sessions[session_id]
            logger.debug(f"[AC-CLARIFY] Session state cleared: session={session_id}")
    
    @classmethod
    def has_active_clarify(cls, session_id: str) -> bool:
        state = cls._sessions.get(session_id)
        if state:
            return not state.is_max_retry()
        return False