AI 사무국

# GPAI 모델 등록 준비 체크리스트
from dataclasses import dataclass
from typing import List, Optional
from enum import Enum

class GPAIRiskCategory(Enum):
    STANDARD = "standard"           # 일반 GPAI
    SYSTEMIC_RISK = "systemic_risk" # 시스템적 위험 GPAI

@dataclass
class GPAIModelRegistration:
    """EU AI Office GPAI 모델 등록 정보"""
    model_name: str
    provider_name: str
    provider_address: str
    eu_representative: Optional[str]  # EU 외 기업 필수
    training_compute_flops: float
    risk_category: GPAIRiskCategory

    # 필수 문서
    technical_documentation: bool = False
    training_data_summary: bool = False
    copyright_policy: bool = False
    energy_consumption_report: bool = False

    # 시스템적 위험 모델 추가 요구사항
    model_evaluation_report: Optional[bool] = None
    adversarial_testing_report: Optional[bool] = None
    risk_mitigation_measures: Optional[bool] = None
    incident_reporting_mechanism: Optional[bool] = None

    def determine_risk_category(self) -> GPAIRiskCategory:
        """학습 연산량 기준 위험 분류"""
        # 10^25 FLOP 이상 = 시스템적 위험
        SYSTEMIC_RISK_THRESHOLD = 10 ** 25
        if self.training_compute_flops >= SYSTEMIC_RISK_THRESHOLD:
            return GPAIRiskCategory.SYSTEMIC_RISK
        return GPAIRiskCategory.STANDARD

    def check_standard_compliance(self) -> dict:
        """일반 GPAI 규정 준수 확인"""
        return {
            "기술문서 작성": self.technical_documentation,
            "학습 데이터 요약": self.training_data_summary,
            "저작권 정책": self.copyright_policy,
            "에너지 소비 보고": self.energy_consumption_report,
            "모든 요건 충족": all([
                self.technical_documentation,
                self.training_data_summary,
                self.copyright_policy,
                self.energy_consumption_report
            ])
        }

    def check_systemic_risk_compliance(self) -> dict:
        """시스템적 위험 GPAI 추가 요건 확인"""
        if self.risk_category != GPAIRiskCategory.SYSTEMIC_RISK:
            return {"해당없음": True}

        return {
            "모델 평가 보고서": self.model_evaluation_report,
            "적대적 테스트 보고서": self.adversarial_testing_report,
            "위험 완화 조치": self.risk_mitigation_measures,
            "사고 보고 체계": self.incident_reporting_mechanism,
            "모든 추가 요건 충족": all([
                self.model_evaluation_report,
                self.adversarial_testing_report,
                self.risk_mitigation_measures,
                self.incident_reporting_mechanism
            ])
        }

    def generate_registration_summary(self) -> dict:
        """AI Office 제출용 등록 요약"""
        return {
            "provider": {
                "name": self.provider_name,
                "address": self.provider_address,
                "eu_representative": self.eu_representative
            },
            "model": {
                "name": self.model_name,
                "training_compute": f"{self.training_compute_flops:.2e} FLOP",
                "risk_category": self.risk_category.value
            },
            "compliance": {
                "standard_requirements": self.check_standard_compliance(),
                "systemic_risk_requirements": self.check_systemic_risk_compliance()
            },
            "registration_ready": self._is_ready_for_submission()
        }

    def _is_ready_for_submission(self) -> bool:
        """등록 제출 준비 완료 여부"""
        standard_ok = self.check_standard_compliance()["모든 요건 충족"]
        if self.risk_category == GPAIRiskCategory.SYSTEMIC_RISK:
            systemic_ok = self.check_systemic_risk_compliance()["모든 추가 요건 충족"]
            return standard_ok and systemic_ok
        return standard_ok

# 사용 예시
model = GPAIModelRegistration(
    model_name="KAITRUST-LLM-70B",
    provider_name="KAITRUST Corp",
    provider_address="Seoul, Korea",
    eu_representative="KAITRUST EU GmbH, Berlin",
    training_compute_flops=5e24,  # 10^25 미만 = 일반 GPAI
    risk_category=GPAIRiskCategory.STANDARD,
    technical_documentation=True,
    training_data_summary=True,
    copyright_policy=True,
    energy_consumption_report=True
)

print(model.generate_registration_summary())