capture-api-response-test-fixture

作成者： vercel

API応答テストフィクスチャを保存・管理し、プロバイダーのパース検証を行います。フィクスチャはプロバイダーパッケージ内の__fixtures__サブフォルダに整理され、既存の例に記載された命名規則に従います。generateText（生の応答をコンソールに記録し、フィクスチャにコピー）とstreamText（includeRawChunksとsaveRawChunksヘルパーを使用してストリーミングチャンクをキャプチャ）の2つのテストパターンをサポートします。サイズ制約により意味を保持したカットが必要な場合を除き、実際のプロバイダー応答を保存することを推奨します...

npx skills add https://github.com/vercel/ai --skill capture-api-response-test-fixture

ZIPダウンロード GitHub

25.8k

API Response Test Fixtures

For provider response parsing tests, we aim at storing test fixtures with the true responses from the providers (unless they are too large in which case some cutting that does not change semantics is advised).

The fixtures are stored in a __fixtures__ subfolder, e.g. packages/openai/src/responses/__fixtures__. See the file names in packages/openai/src/responses/__fixtures__ for naming conventions and packages/openai/src/responses/openai-responses-language-model.test.ts for how to set up test helpers.

You can use our examples under /examples/ai-functions to generate test fixtures.

generateText (doGenerate testing)

For generateText, log the raw response output to the console and copy it into a new test fixture.

import { openai } from '@ai-sdk/openai';
import { generateText } from 'ai';
import { run } from '../lib/run';

run(async () => {
  const result = await generateText({
    model: openai('gpt-5-nano'),
    prompt: 'Invent a new holiday and describe its traditions.',
  });

  console.log(JSON.stringify(result.response.body, null, 2));
});

streamText (doStream testing)

For streamText, you need to set includeRawChunks to true and use the special saveRawChunks helper. Run the script from the /example/ai-functions folder via pnpm tsx src/stream-text/script-name.ts. The result is then stored in the /examples/ai-functions/output folder. You can copy it to your fixtures folder and rename it.

import { openai } from '@ai-sdk/openai';
import { streamText } from 'ai';
import { run } from '../lib/run';
import { saveRawChunks } from '../lib/save-raw-chunks';

run(async () => {
  const result = streamText({
    model: openai('gpt-5-nano'),
    prompt: 'Invent a new holiday and describe its traditions.',
    includeRawChunks: true,
  });

  await saveRawChunks({ result, filename: 'openai-gpt-5-nano' });
});