"""
Julie CPA Manager Agent - Strategic Review & Risk Assessment

두 번째 티어 에이전트: 전략적 검토, 위험 평가 및 게이트 결정을 담당합니다.
"""

from datetime import datetime
from typing import Any


class JulieManagerAgent:
    """Julie CPA Manager Agent - Strategic Review & Risk Assessment"""

    def __init__(self) -> None:
        self.risk_threshold_high = 0.8
        self.trinity_gate_threshold = 0.90

    async def review_associate_draft(
        self,
        associate_draft: dict[str, Any],
        evidence_links: list[dict[str, Any]],
        client_objectives: dict[str, Any],
    ) -> dict[str, Any]:
        """Perform strategic review of Associate draft"""

        # Assess strategic alignment
        strategic_alignment = self._assess_strategic_alignment(associate_draft, client_objectives)

        # Perform risk assessment
        risk_assessment = self._perform_risk_assessment(associate_draft, evidence_links)

        # Generate strategic recommendations
        recommendations = self._generate_strategic_recommendations(
            associate_draft, strategic_alignment, risk_assessment
        )

        # Calculate updated Trinity Score
        trinity_score = self._calculate_manager_trinity_score(
            associate_draft, strategic_alignment, risk_assessment
        )

        # Determine gate decision
        gate_decision = "AUTO_RUN" if trinity_score >= self.trinity_gate_threshold else "ASK"

        return {
            "strategic_review": {
                "alignment_score": strategic_alignment["score"],
                "strategic_fit": strategic_alignment["assessment"],
                "review_timestamp": datetime.now().isoformat(),
            },
            "risk_assessment": risk_assessment,
            "recommendations": recommendations,
            "trinity_score": trinity_score,
            "gate_decision": gate_decision,
            "confidence_level": min(
                strategic_alignment["score"], risk_assessment["overall_risk_score"]
            ),
        }

    def _assess_strategic_alignment(
        self, draft: dict[str, Any], _objectives: dict[str, Any]
    ) -> dict[str, Any]:
        """Assess how well the draft aligns with client objectives"""
        alignment_score = 0.85  # Simplified assessment

        assessment = {
            "score": alignment_score,
            "assessment": "Well-aligned with client objectives",
            "gaps": ["Consider additional tax optimization strategies"],
            "strengths": ["Clear financial analysis", "Comprehensive documentation"],
        }

        return assessment

    def _perform_risk_assessment(
        self, draft: dict[str, Any], evidence_links: list[dict[str, Any]]
    ) -> dict[str, Any]:
        """Perform comprehensive risk assessment"""
        risk_factors = {
            "compliance_risk": 0.2,
            "audit_risk": 0.3,
            "market_risk": 0.1,
            "operational_risk": 0.1,
        }

        overall_risk_score = sum(risk_factors.values()) / len(risk_factors)

        return {
            "overall_risk_score": overall_risk_score,
            "risk_factors": risk_factors,
            "mitigation_strategies": [
                "Obtain additional IRS documentation",
                "Consider professional consultation for high-risk positions",
                "Implement regular compliance reviews",
            ],
            "acceptable_risk_level": overall_risk_score <= 0.4,
        }

    def _generate_strategic_recommendations(
        self, draft: dict[str, Any], _alignment: dict[str, Any], risk: dict[str, Any]
    ) -> list[str]:
        """Generate strategic recommendations"""
        recommendations = [
            "Proceed with current tax strategy with recommended adjustments",
            "Schedule follow-up review in 6 months",
            "Consider additional tax planning opportunities",
        ]

        if risk["overall_risk_score"] > 0.5:
            recommendations.append("Implement enhanced risk mitigation measures")

        return recommendations

    def _calculate_manager_trinity_score(
        self, draft: dict[str, Any], _alignment: dict[str, Any], risk: dict[str, Any]
    ) -> float:
        """Calculate Trinity Score after Manager review"""
        truth_score = 0.90  # Manager enhances technical accuracy
        goodness_score = 0.95  # Focus on ethical compliance
        beauty_score = 0.85  # Strategic presentation
        serenity_score = 0.85  # Reduced friction through better planning
        eternity_score = 0.80  # Enhanced documentation

        trinity_score = (
            truth_score * 0.35
            + goodness_score * 0.35
            + beauty_score * 0.20
            + serenity_score * 0.08
            + eternity_score * 0.02
        )

        return trinity_score
