develop-ai-functions-example

by vercel

Develop examples for AI SDK functions. Use when creating, running, or modifying examples under examples/ai-functions/src to validate provider support,… npx skills add https://github.com/vercel-labs/ai --skill develop-ai-functions-example Download ZIPGitHub25.4k

AI Functions Examples

The examples/ai-functions/ directory contains scripts for validating, testing, and iterating on AI SDK functions across providers.

Example Categories

Examples are organized by AI SDK function in examples/ai-functions/src/:

Directory Purpose generate-text/ Non-streaming text generation with generateText() stream-text/ Streaming text generation with streamText() generate-object/ Structured output generation with generateObject() stream-object/ Streaming structured output with streamObject() agent/ ToolLoopAgent examples for agentic workflows embed/ Single embedding generation with embed() embed-many/ Batch embedding generation with embedMany() generate-image/ Image generation with generateImage() generate-speech/ Text-to-speech with generateSpeech() transcribe/ Audio transcription with transcribe() rerank/ Document reranking with rerank() middleware/ Custom middleware implementations registry/ Provider registry setup and usage telemetry/ OpenTelemetry integration complex/ Multi-component examples (agents, routers) lib/ Shared utilities (not examples) tools/ Reusable tool definitions

File Naming Convention

Examples follow the pattern: {provider}-{feature}.ts

Pattern Example Description {provider}.ts openai.ts Basic provider usage {provider}-{feature}.ts openai-tool-call.ts Specific feature {provider}-{sub-provider}.ts amazon-bedrock-anthropic.ts Provider with sub-provider {provider}-{sub-provider}-{feature}.ts google-vertex-anthropic-cache-control.ts Sub-provider with feature

Example Structure

All examples use the run() wrapper from lib/run.ts which:

• Loads environment variables from .env

• Provides error handling with detailed API error logging

Basic Template

import { providerName } from '@ai-sdk/provider-name';
import { generateText } from 'ai';
import { run } from '../lib/run';

run(async () => {
 const result = await generateText({
 model: providerName('model-id'),
 prompt: 'Your prompt here.',
 });

 console.log(result.text);
 console.log('Token usage:', result.usage);
 console.log('Finish reason:', result.finishReason);
});

Streaming Template

import { providerName } from '@ai-sdk/provider-name';
import { streamText } from 'ai';
import { printFullStream } from '../lib/print-full-stream';
import { run } from '../lib/run';

run(async () => {
 const result = streamText({
 model: providerName('model-id'),
 prompt: 'Your prompt here.',
 });

 await printFullStream({ result });
});

Tool Calling Template

import { providerName } from '@ai-sdk/provider-name';
import { generateText, tool } from 'ai';
import { z } from 'zod';
import { run } from '../lib/run';

run(async () => {
 const result = await generateText({
 model: providerName('model-id'),
 tools: {
 myTool: tool({
 description: 'Tool description',
 inputSchema: z.object({
 param: z.string().describe('Parameter description'),
 }),
 execute: async ({ param }) => {
 return { result: `Processed: ${param}` };
 },
 }),
 },
 prompt: 'Use the tool to...',
 });

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

Structured Output Template

import { providerName } from '@ai-sdk/provider-name';
import { generateObject } from 'ai';
import { z } from 'zod';
import { run } from '../lib/run';

run(async () => {
 const result = await generateObject({
 model: providerName('model-id'),
 schema: z.object({
 name: z.string(),
 items: z.array(z.string()),
 }),
 prompt: 'Generate a...',
 });

 console.log(JSON.stringify(result.object, null, 2));
 console.log('Token usage:', result.usage);
});

When to Write Examples

Write examples when:

Adding a new provider: Create basic examples for each supported API (generateText, streamText, generateObject, etc.)

Implementing a new feature: Demonstrate the feature with at least one provider example

Reproducing a bug: Create an example that shows the issue for debugging

Adding provider-specific options: Show how to use providerOptions for provider-specific settings

Creating test fixtures: Use examples to generate API response fixtures (see capture-api-response-test-fixture skill)

Utility Helpers

The lib/ directory contains shared utilities:

File Purpose run.ts Error-handling wrapper with .env loading print.ts Clean object printing (removes undefined values) print-full-stream.ts Colored streaming output for tool calls, reasoning, text save-raw-chunks.ts Save streaming chunks for test fixtures present-image.ts Display images in terminal save-audio.ts Save audio files to disk

Using print utilities

import { print } from '../lib/print';

// Pretty print objects without undefined values
print('Result:', result);
print('Usage:', result.usage, { depth: 2 });

Using printFullStream

import { printFullStream } from '../lib/print-full-stream';

const result = streamText({ ... });
await printFullStream({ result }); // Colored output for text, tool calls, reasoning

Reusable Tools

The tools/ directory contains reusable tool definitions:

import { weatherTool } from '../tools/weather-tool';

const result = await generateText({
 model: openai('gpt-4o'),
 tools: { weather: weatherTool },
 prompt: 'What is the weather in San Francisco?',
});

Best Practices

Keep examples focused: Each example should demonstrate one feature or use case

Use descriptive prompts: Make it clear what the example is testing

Handle errors gracefully: The run() wrapper handles this automatically

Use realistic model IDs: Use actual model IDs that work with the provider

Add comments for complex logic: Explain non-obvious code patterns

Reuse tools when appropriate: Use weatherTool or create new reusable tools in tools/