capture-api-response-test-fixture
GitHub指导如何生成并存储 API 响应测试用例,涵盖 generateText 和 streamText 场景。提供脚本编写示例及文件存放规范,用于确保 Provider 响应解析测试的准确性与一致性。
Trigger Scenarios
Install
npx skills add vercel/ai --skill capture-api-response-test-fixture -g -y
SKILL.md
Frontmatter
{
"name": "capture-api-response-test-fixture",
"metadata": {
"internal": true
},
"description": "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, 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' });
});
Version History
-
1d9b13b
Current 2026-08-29 05:28
改进了 provider 包指南,对齐了 AI Functions 示例和 fixture 技能以符合嵌套目录约定;增加了官方 OpenAPI 发现指导。
- c0595b4 2026-08-20 17:57


