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); });
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 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/