capture-api-response-test-fixture
Almacenar y gestionar fixtures de prueba de respuestas de API para la validación de análisis de proveedores. Los fixtures se organizan en subcarpetas __fixtures__ dentro de los paquetes de proveedores, utilizando convenciones de nomenclatura documentadas en ejemplos existentes. Soporta dos patrones de prueba: generateText (registrar la respuesta sin procesar en la consola y copiarla en el fixture) y streamText (usar los ayudantes includeRawChunks y saveRawChunks para capturar fragmentos de streaming). Recomienda almacenar respuestas reales del proveedor a menos que las restricciones de tamaño requieran recortes que preserven el significado semántico...
npx skills add https://github.com/vercel/ai --skill capture-api-response-test-fixtureAPI 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' });
});