
AI Functions Examples
OfficialFreeValidate and demonstrate AI SDK functions with ease.
Free · Opens the source repo
What AI Functions Examples does
The AI Functions Examples skill provides a structured way to create, run, and validate examples of various AI SDK functions across different providers. It is particularly useful for developers working with AI APIs, allowing them to quickly set up examples that showcase the capabilities of these SDKs. The examples are organized by function, making it easy to find and use the relevant scripts for tasks such as text generation, audio transcription, and image creation.
Within the examples/ai-functions/src/ directory, you'll find a variety of categories, each dedicated to specific functionalities of the AI SDK. For instance, you can explore non-streaming and streaming text generation, structured output generation, and even agent workflows. This organization not only aids in understanding the different capabilities of the SDK but also facilitates the testing and validation of provider support for these functions.
The skill also includes a robust example structure, utilizing a consistent file naming convention that helps in identifying the provider and feature at a glance. Each example is wrapped in a run() function that handles environment variable loading and error logging, ensuring that developers can focus on implementing and testing their AI functionalities without getting bogged down by setup issues. This makes it an excellent resource for both new and experienced developers looking to streamline their workflow when working with AI SDKs.
Overall, this skill is essential for anyone involved in developing or testing AI applications, providing a comprehensive set of examples that can be easily adapted to meet specific needs.
When to use it
Use this skill when you need to create, run, or modify examples for AI SDK functions, especially when validating provider capabilities.
When not to use it
This skill is not suitable for general-purpose coding tasks outside of AI SDK function examples or for users unfamiliar with TypeScript.
What you can build with it
Creating a New Provider Example
When adding support for a new AI provider, use the skill to quickly create examples for core functions like `generateText` and `streamText`.
Demonstrating a New Feature
If you implement a new feature in your AI application, create an example to showcase its functionality and how it integrates with existing providers.
Debugging an Issue
When encountering a bug, write a specific example that reproduces the issue, which can help in diagnosing the problem more effectively.
How to install AI Functions Examples
View source1. Install with the skills CLI
npx skills add vercel/ai/develop-ai-functions-example --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by vercelAI 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);
});
Running Examples
From the examples/ai-functions directory:
pnpm tsx src/generate-text/openai.ts
pnpm tsx src/stream-text/openai-tool-call.ts
pnpm tsx src/agent/openai-generate.ts
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
providerOptionsfor provider-specific settings -
Creating test fixtures: Use examples to generate API response fixtures (see
capture-api-response-test-fixtureskill)
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
weatherToolor create new reusable tools intools/
Frequently asked questions about AI Functions Examples
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