matrix.test.ts

/*
 * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
 * or more contributor license agreements. Licensed under the Elastic License
 * 2.0; you may not use this file except in compliance with the Elastic License
 * 2.0.
 */

import { buildMatrix } from '../../matrix/build_matrix';
import { renderMatrix } from '../../matrix/render_matrix';
import { parseMatrixConfig } from '../../matrix/load_matrix_config';
import type { AggregatedModelScores } from '../../matrix/query_matrix_scores';

describe('matrix command empty-result guard', () => {
  const config = parseMatrixConfig({
    columns: [{ id: 'triage', label: 'Triage', suites: ['suite-a'], weight: 1 }],
    models: [{ id: 'model-a', label: 'Model A' }],
  });

  it('renders header-only CSVs when no experiments match', () => {
    const rendered = renderMatrix(buildMatrix([], config), config);

    expect(rendered.proprietaryCsv.trim().split('\n')).toHaveLength(1);
    expect(rendered.openSourceCsv.trim().split('\n')).toHaveLength(1);
  });

  it('renders populated CSVs when experiments do match', () => {
    const aggregated: AggregatedModelScores[] = [
      {
        modelId: 'model-a',
        provider: 'anthropic',
        suites: [
          {
            suiteId: 'suite-a',
            experimentId: 'experiment-a',
            datasets: [
              {
                datasetId: 'dataset-a-id',
                datasetName: 'dataset-a',
                evaluators: [{ evaluatorName: 'correctness', mean: 0.9, count: 10 }],
              },
            ],
          },
        ],
      },
    ];

    const rendered = renderMatrix(buildMatrix(aggregated, config), config);

    expect(rendered.proprietaryCsv.trim().split('\n').length).toBeGreaterThan(1);
  });

  it('produces no model rows when no experiments match', () => {
    const matrix = buildMatrix([], config);

    expect(matrix.proprietary).toHaveLength(0);
    expect(matrix.openSource).toHaveLength(0);
  });
});