"""Safety/Bias Checks Router"""
from fastapi import APIRouter, UploadFile, File
from pydantic import BaseModel
from typing import Optional

router = APIRouter()


class BiasMetrics(BaseModel):
    demographic_parity: float
    equalized_odds: float
    calibration_error: float
    disparate_impact: float


class FairnessReport(BaseModel):
    protected_attribute: str
    groups: list[str]
    metrics: BiasMetrics
    is_fair: bool
    violations: list[str]
    recommendations: list[str]


class ComplianceChecklist(BaseModel):
    regulation: str  # GDPR, CCPA, AI Act, etc.
    checks: list[dict]
    passed: int
    failed: int
    overall_status: str


@router.post("/analyze", response_model=FairnessReport)
async def analyze_bias(
    file: UploadFile = File(...),
    target_column: str = None,
    protected_attribute: str = None,
    favorable_outcome: str = None
):
    """Analyze model predictions for bias"""
    # TODO: Implement bias analysis with Fairlearn
    return FairnessReport(
        protected_attribute=protected_attribute or "unknown",
        groups=[],
        metrics=BiasMetrics(
            demographic_parity=0.0,
            equalized_odds=0.0,
            calibration_error=0.0,
            disparate_impact=0.0
        ),
        is_fair=True,
        violations=[],
        recommendations=[]
    )


@router.post("/compliance-check", response_model=ComplianceChecklist)
async def check_compliance(
    regulation: str = "gdpr",
    model_info: dict = None
):
    """Run compliance checklist for a regulation"""
    # TODO: Implement compliance checking
    return ComplianceChecklist(
        regulation=regulation,
        checks=[],
        passed=0,
        failed=0,
        overall_status="unknown"
    )


@router.get("/regulations")
async def list_regulations():
    """List supported regulations and frameworks"""
    return {
        "regulations": [
            {"code": "gdpr", "name": "EU GDPR", "checks": 15},
            {"code": "ccpa", "name": "California CCPA", "checks": 10},
            {"code": "ai_act", "name": "EU AI Act", "checks": 20},
            {"code": "nist", "name": "NIST AI RMF", "checks": 25},
        ]
    }


@router.get("/metrics")
async def list_fairness_metrics():
    """List available fairness metrics with explanations"""
    return {
        "metrics": [
            {"name": "demographic_parity", "description": "Equal positive prediction rates across groups"},
            {"name": "equalized_odds", "description": "Equal TPR and FPR across groups"},
            {"name": "calibration", "description": "Predicted probabilities match actual outcomes"},
            {"name": "disparate_impact", "description": "Ratio of positive rates (80% rule)"},
        ]
    }
