export const CREDITS_PER_CNY = 10;
export const CONSULTATION_DOMAIN_DURATION_MS = 21_000;
const MICROUSD_PER_USD = 1_000_000;

export type Metric = Readonly<{ runs: number; avg: number | null; p50: number | null; p95: number | null; max: number | null }>;
export type UsageAggregate = Readonly<{
  hasData: boolean;
  metrics: Readonly<{ costMicrousd: Metric; inputTokens: Metric; outputTokens: Metric; durationMs: Metric }>;
}>;
export type ModelPrice = Readonly<{
  modelTier: string;
  inputCostMicrousdPerMillion: number;
  outputCostMicrousdPerMillion: number;
}>;
export type DistributionBand = Readonly<{ weight: number; monthlyMessages: number }>;

export type FeatureSimulationInput = Readonly<{
  featureKey: string;
  creditCost: number | null;
  model: ModelPrice | null;
  usage: UsageAggregate | null;
  usdToCny: number | null;
}>;

export type FeatureSimulation = Readonly<{
  featureKey: string;
  saleCny: number | null;
  costMicrousd: number | null;
  costCny: number | null;
  marginPercent: number | null;
  source: "ledger" | "model_estimate" | "unavailable";
}>;

function metricValue(metric: Metric, percentile: "p50" | "p95" | "max"): number | null {
  return metric[percentile];
}

export function estimateFeature(input: FeatureSimulationInput, percentile: "p50" | "p95" | "max" = "p50"): FeatureSimulation {
  const saleCny = input.creditCost === null ? null : input.creditCost / CREDITS_PER_CNY;
  if (input.creditCost === null || !input.usage?.hasData) {
    return { featureKey: input.featureKey, saleCny, costMicrousd: null, costCny: null, marginPercent: null, source: "unavailable" };
  }

  const observedCost = metricValue(input.usage.metrics.costMicrousd, percentile);
  const modelCost = input.model && input.usage.metrics.inputTokens[percentile] !== null && input.usage.metrics.outputTokens[percentile] !== null
    ? (input.usage.metrics.inputTokens[percentile]! * input.model.inputCostMicrousdPerMillion
      + input.usage.metrics.outputTokens[percentile]! * input.model.outputCostMicrousdPerMillion) / 1_000_000
    : null;
  const costMicrousd = observedCost ?? modelCost;
  const costCny = costMicrousd === null || input.usdToCny === null
    ? null
    : (costMicrousd / MICROUSD_PER_USD) * input.usdToCny;
  return {
    featureKey: input.featureKey,
    saleCny,
    costMicrousd,
    costCny,
    marginPercent: costCny === null || saleCny === null || saleCny === 0 ? null : ((saleCny - costCny) / saleCny) * 100,
    source: observedCost !== null ? "ledger" : costMicrousd === null ? "unavailable" : "model_estimate",
  };
}

export function weightedAverageMessages(distribution: readonly DistributionBand[]): number | null {
  const usable = distribution.filter((band) => Number.isFinite(band.weight) && band.weight > 0 && Number.isFinite(band.monthlyMessages));
  const totalWeight = usable.reduce((sum, band) => sum + band.weight, 0);
  if (totalWeight <= 0) return null;
  return usable.reduce((sum, band) => sum + (band.weight / totalWeight) * Math.max(0, band.monthlyMessages), 0);
}

// billingLimit is an anomaly-account circuit breaker, not the member-facing total allowance.
export function membershipCost(distribution: readonly DistributionBand[], unitCostCny: number | null, billingLimit: number | null) {
  const averageMessages = weightedAverageMessages(distribution);
  return {
    averageMessages,
    averageCostCny: averageMessages === null || unitCostCny === null ? null : averageMessages * unitCostCny,
    worstCostCny: billingLimit === null || unitCostCny === null ? null : billingLimit * unitCostCny,
    unlimitedWorstCase: billingLimit === null,
  };
}

export function dailySerialCapacity(durationMs = CONSULTATION_DOMAIN_DURATION_MS): number | null {
  if (!Number.isFinite(durationMs) || durationMs <= 0) return null;
  return Math.floor(86_400_000 / durationMs);
}

export function memberCapacity(distribution: readonly DistributionBand[], unitDurationMs: number): number | null {
  const averageMessages = weightedAverageMessages(distribution);
  const dailyCapacity = dailySerialCapacity(unitDurationMs);
  if (averageMessages === null || dailyCapacity === null || averageMessages <= 0) return null;
  return Math.floor(dailyCapacity / (averageMessages / 30));
}