import { describe, it, expect } from 'vitest';
import { episodeUsd, aggregateDay } from './cost-aggregator.mjs';
import { PRICING } from './cost-pricing.mjs';

describe('episodeUsd', () => {
  it('returns all-zero object for empty/missing task_cost', () => {
    const u = episodeUsd({}, PRICING);
    expect(u.classifier_usd).toBe(0);
    expect(u.self_assessment_usd).toBe(0);
    expect(u.reviewer_subagent_usd).toBe(0);
    expect(u.reviewer_direct_fallback_usd).toBe(0);
    expect(u.self_retrospect_usd).toBe(0);
    expect(u.total_usd).toBe(0);
  });

  it('includes judge_spend_usd in episodeUsd + total', () => {
    const ep = { task_cost: { judge_spend_usd: 0.002 } };
    const u = episodeUsd(ep, PRICING);
    expect(u.judge_spend_usd).toBe(0.002);
    expect(u.total_usd).toBeCloseTo(0.002, 9);
  });

  it('computes classifier_usd from sonnet pricing', () => {
    const ep = { task_cost: { classifier_input_tokens: 1_000_000, classifier_output_tokens: 100_000 } };
    const u = episodeUsd(ep, PRICING);
    // 1M × $3 + 100k × $15 = $3 + $1.5 = $4.5
    expect(u.classifier_usd).toBeCloseTo(4.5, 6);
  });

  it('computes self_assessment_usd from opus pricing', () => {
    const ep = { task_cost: { self_assessment_input_tokens: 1_000_000, self_assessment_output_tokens: 10_000 } };
    const u = episodeUsd(ep, PRICING);
    // 1M × $15 + 10k × $75 = $15 + $0.75 = $15.75
    expect(u.self_assessment_usd).toBeCloseTo(15.75, 6);
  });

  it('sums reviewer_subagent_usd and reviewer_direct_fallback_usd as-is', () => {
    const ep = { task_cost: { reviewer_subagent_usd: 0.5, reviewer_direct_fallback_usd: 0.05 } };
    const u = episodeUsd(ep, PRICING);
    expect(u.reviewer_subagent_usd).toBe(0.5);
    expect(u.reviewer_direct_fallback_usd).toBe(0.05);
  });

  it('reads self_retrospect_usd if present, defaults to 0', () => {
    const ep1 = { task_cost: { self_retrospect_usd: 2.0 } };
    expect(episodeUsd(ep1, PRICING).self_retrospect_usd).toBe(2.0);
    const ep2 = { task_cost: {} };
    expect(episodeUsd(ep2, PRICING).self_retrospect_usd).toBe(0);
  });

  it('total_usd is sum of all 5 components', () => {
    const ep = { task_cost: {
      classifier_input_tokens: 1_000_000,        // $3
      classifier_output_tokens: 0,
      self_assessment_input_tokens: 0,
      self_assessment_output_tokens: 100_000,    // $7.5
      reviewer_subagent_usd: 0.5,
      reviewer_direct_fallback_usd: 0.05,
      self_retrospect_usd: 1.0,
    } };
    const u = episodeUsd(ep, PRICING);
    // 3 + 7.5 + 0.5 + 0.05 + 1.0 = 12.05
    expect(u.total_usd).toBeCloseTo(12.05, 6);
  });
});

describe('aggregateDay', () => {
  const epOn = (date, cost) => ({
    timestamps: { started_at: `${date}T12:00:00.000Z` },
    task_cost: cost,
  });

  it('returns zero-day object when no episodes match date', () => {
    const result = aggregateDay([epOn('2026-05-27', {})], '2026-05-28', PRICING);
    expect(result.episode_count).toBe(0);
    expect(result.total_usd).toBe(0);
  });

  it('counts only episodes whose started_at starts with the given date', () => {
    const episodes = [
      epOn('2026-05-28', { classifier_input_tokens: 1_000_000 }),       // $3
      epOn('2026-05-28', { self_assessment_output_tokens: 100_000 }),   // $7.5
      epOn('2026-05-27', { classifier_input_tokens: 1_000_000 }),       // EXCLUDED
      epOn('2026-05-29', { classifier_input_tokens: 1_000_000 }),       // EXCLUDED
    ];
    const r = aggregateDay(episodes, '2026-05-28', PRICING);
    expect(r.episode_count).toBe(2);
    expect(r.classifier_usd).toBeCloseTo(3, 6);
    expect(r.self_assessment_usd).toBeCloseTo(7.5, 6);
    expect(r.total_usd).toBeCloseTo(10.5, 6);
  });

  it('skips malformed episodes (no timestamps / non-string started_at)', () => {
    const episodes = [
      null,
      {},
      { timestamps: null },
      { timestamps: { started_at: 42 } },
      epOn('2026-05-28', { classifier_input_tokens: 1_000_000 }),       // $3
    ];
    const r = aggregateDay(episodes, '2026-05-28', PRICING);
    expect(r.episode_count).toBe(1);
    expect(r.classifier_usd).toBeCloseTo(3, 6);
  });

  it('returns object with exactly 8 keys (6 components + total + count)', () => {
    const r = aggregateDay([], '2026-05-28', PRICING);
    expect(Object.keys(r).sort()).toEqual([
      'classifier_usd',
      'episode_count',
      'judge_spend_usd',
      'reviewer_direct_fallback_usd',
      'reviewer_subagent_usd',
      'self_assessment_usd',
      'self_retrospect_usd',
      'total_usd',
    ]);
  });
});