develop-ai-functions-example

name	develop-ai-functions-example
description	Develop examples for AI SDK functions. Use when creating, running, or modifying examples under examples/ai-functions/src to validate provider support, demonstrate features, or create test fixtures.
metadata	{"internal":true}

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

Group examples by function and provider. Name the entry example basic.ts and use descriptive kebab-case.ts names for additional examples:

Pattern	Example	Description
<function>/<provider>/basic.ts	generate-text/openai/basic.ts	Basic provider usage
<function>/<provider>/<feature>.ts	stream-text/openai/tool-call.ts	Specific feature
<function>/<provider>/<sub-provider>.ts	stream-text/amazon-bedrock/anthropic.ts	Provider with sub-provider
<function>/<provider>/<sub-provider>-<feature>.ts	stream-text/google/vertex-anthropic-cache-control.ts	Sub-provider with feature

Do not create flat provider files such as generate-text/openai.ts.

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/basic.ts
pnpm tsx src/stream-text/openai/tool-call.ts
pnpm tsx src/agent/openai/generate.ts

When to Write Examples

Write examples when:

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

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

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

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

5. 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

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

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

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

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

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

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