Claude-skill-registry capture-api-response-test-fixture

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' });
});