develop-ai-functions-example

Original：🇺🇸 English
Translated

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.

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Tags

Translated version includes tags in frontmatter
ai-sdk-examplesai-functionsprovider-integrationtest-fixturestool-calling

SKILL.md Content

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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/
:
DirectoryPurpose
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
PatternExampleDescription
{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

typescript
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

typescript
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

typescript
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

typescript
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:
bash
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:
  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:
FilePurpose
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

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

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

Using printFullStream

typescript
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:
typescript
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/