capture-api-response-test-fixture

par vercel

Stocker et gérer des fixtures de réponses API pour la validation du parsing des fournisseurs. Les fixtures sont organisées dans des sous-dossiers __fixtures__ au sein des packages fournisseurs, en utilisant des conventions de nommage documentées dans les exemples existants. Prend en charge deux modèles de test : generateText (journaliser la réponse brute dans la console et la copier dans la fixture) et streamText (utiliser les helpers includeRawChunks et saveRawChunks pour capturer les chunks de streaming). Recommande de stocker les vraies réponses des fournisseurs, sauf si des contraintes de taille nécessitent des coupures préservant le sens...

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

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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, put the script under src/generate-text/<provider>/, 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. Put the script under the provider directory and run it from the /examples/ai-functions folder via pnpm tsx src/stream-text/<provider>/<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' });
});