ai-sdk-6-skills

Links

AI SDK 6 Beta Docs: https://v6.ai-sdk.dev/docs/announcing-ai-sdk-6-beta
Groq Provider: https://v6.ai-sdk.dev/providers/ai-sdk-providers/groq
Vercel AI Gateway: https://v6.ai-sdk.dev/providers/ai-sdk-providers/ai-gateway
AI SDK GitHub: https://github.com/vercel/ai
Groq Console Models: https://console.groq.com/docs/models

Installation

pnpm add ai@beta @ai-sdk/openai@beta @ai-sdk/react@beta @ai-sdk/groq@beta

Note: Pin versions during beta as breaking changes may occur in patch releases.

What's New in AI SDK 6?

1. Agent Abstraction (New)

Unified interface for building agents with full control over execution flow, tool loops, and state management.

typescript

import { ToolLoopAgent } from 'ai';
import { tool } from 'ai';
import { z } from 'zod';

const weatherTool = tool({
  description: 'Get weather for a location',
  inputSchema: z.object({ city: z.string() }),
  execute: async ({ city }) => ({ temperature: 72, condition: 'sunny' }),
});

const agent = new ToolLoopAgent({
  model: 'groq/llama-3.3-70b-versatile', // or any model
  instructions: 'You are a helpful weather assistant.',
  tools: { weather: weatherTool },
});

// Use the agent
const result = await agent.generate({
  prompt: 'What is the weather in San Francisco?',
});

console.log(result.output);

2. Tool Execution Approval (New)

Request user confirmation before executing sensitive tools.

typescript

import { tool } from 'ai';
import { z } from 'zod';

const paymentTool = tool({
  description: 'Process a payment',
  inputSchema: z.object({
    amount: z.number(),
    recipient: z.string(),
  }),
  needsApproval: true, // Require approval
  execute: async ({ amount, recipient }) => {
    return { success: true, id: 'txn-123' };
  },
});

Client-side approval UI:

typescript

export function PaymentToolView({ invocation, addToolApprovalResponse }) {
  if (invocation.state === 'approval-requested') {
    return (
      <div>
        <p>Process payment of ${invocation.input.amount} to {invocation.input.recipient}?</p>
        <button
          onClick={() =>
            addToolApprovalResponse({
              id: invocation.approval.id,
              approved: true,
            })
          }
        >
          Approve
        </button>
        <button
          onClick={() =>
            addToolApprovalResponse({
              id: invocation.approval.id,
              approved: false,
            })
          }
        >
          Deny
        </button>
      </div>
    );
  }
  return null;
}

3. Structured Output + Tool Calling (Stable)

Combine tool calling with structured output generation:

typescript

import { ToolLoopAgent, Output } from 'ai';
import { z } from 'zod';

const agent = new ToolLoopAgent({
  model: 'groq/llama-3.3-70b-versatile',
  tools: { /* ... */ },
  output: Output.object({
    schema: z.object({
      summary: z.string(),
      temperature: z.number(),
      recommendation: z.string(),
    }),
  }),
});

const { output } = await agent.generate({
  prompt: 'What is the weather in San Francisco and what should I wear?',
});

console.log(output);
// { summary: '...', temperature: 72, recommendation: '...' }

4. Reranking Support (New)

Improve search relevance by reordering documents:

typescript

import { rerank } from 'ai';
import { cohere } from '@ai-sdk/cohere';

const { ranking } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: [
    'sunny day at the beach',
    'rainy afternoon in the city',
    'snowy night in the mountains',
  ],
  query: 'talk about rain',
  topN: 2,
});

console.log(ranking);
// [
//   { originalIndex: 1, score: 0.9, document: 'rainy afternoon...' },
//   { originalIndex: 0, score: 0.3, document: 'sunny day...' }
// ]

Migration from AI SDK 5

Minimal breaking changes expected. Most AI SDK 5 code will work with little modification.

Key differences:

Agent abstraction replaces ad-hoc patterns; consider migrating to
```
ToolLoopAgent
```
.
Structured output now works with
```
generateText
```
/
```
streamText
```
(requires
```
stopWhen
```
).
```
@ai-sdk/*
```
packages may have minor API adjustments during beta.

Groq Provider (Open Weight Models)

Setup

pnpm add @ai-sdk/groq

Environment:

env

GROQ_API_KEY=your_groq_api_key

Open Weight Models Available

Popular Groq models for AI SDK 6:

```
llama-3.3-70b-versatile
```
(Llama 3.3, 70B, balanced)
```
llama-3.1-8b-instant
```
(Llama 3.1, 8B, fast)
```
mixtral-8x7b-32768
```
(Mixture of Experts)
```
gemma2-9b-it
```
(Google Gemma 2)
```
qwen/qwen3-32b
```
(Qwen 3)

See Groq console for full list.

Basic Llama Example

typescript

import { groq } from '@ai-sdk/groq';
import { generateText } from 'ai';

const { text } = await generateText({
  model: groq('llama-3.3-70b-versatile'),
  prompt: 'Write a TypeScript function to compute Fibonacci.',
});

console.log(text);

Structured Output with Llama (Groq)

typescript

import { groq } from '@ai-sdk/groq';
import { generateObject } from 'ai';
import { z } from 'zod';

const result = await generateObject({
  model: groq('llama-3.3-70b-versatile'),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(z.string()),
      instructions: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a simple pasta recipe.',
  providerOptions: {
    groq: {
      structuredOutputs: true, // Enable for supported models
    },
  },
});

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

Tool Use with Llama (Groq)

typescript

import { groq } from '@ai-sdk/groq';
import { generateText, tool } from 'ai';
import { z } from 'zod';

const weatherTool = tool({
  description: 'Get weather for a city',
  inputSchema: z.object({ city: z.string() }),
  execute: async ({ city }) => ({ temp: 72, condition: 'sunny' }),
});

const { text } = await generateText({
  model: groq('llama-3.3-70b-versatile'),
  prompt: 'What is the weather in NYC and LA?',
  tools: { weather: weatherTool },
});

console.log(text);

Reasoning Models (Groq)

Groq offers reasoning models like

qwen/qwen3-32b

and

deepseek-r1-distill-llama-70b

typescript

import { groq } from '@ai-sdk/groq';
import { generateText } from 'ai';

const { text } = await generateText({
  model: groq('qwen/qwen3-32b'),
  providerOptions: {
    groq: {
      reasoningFormat: 'parsed', // 'parsed', 'hidden', or 'raw'
      reasoningEffort: 'default', // low, medium, high
    },
  },
  prompt: 'How many "r"s are in the word "strawberry"?',
});

console.log(text);

Image Input with Llama (Groq Multi-Modal)

typescript

import { groq } from '@ai-sdk/groq';
import { generateText } from 'ai';

const { text } = await generateText({
  model: groq('meta-llama/llama-4-scout-17b-16e-instruct'), // Multi-modal model
  messages: [
    {
      role: 'user',
      content: [
        { type: 'text', text: 'What is in this image?' },
        { type: 'image', image: 'https://example.com/image.jpg' },
      ],
    },
  ],
});

console.log(text);

Vercel AI Gateway

What It Is

A unified interface to access models from 20+ providers (OpenAI, Anthropic, Google, Groq, xAI, Mistral, etc.) through a single API. Requires Vercel account and credit card.

Setup

env

AI_GATEWAY_API_KEY=your_gateway_api_key

Get your key from Vercel Dashboard > AI Gateway.

⚠️ Note: Credit card required for Gateway usage. You will be billed for model calls routed through the gateway.

Authentication

API Key Authentication

Set via environment variable or directly in code:

typescript

import { createGateway } from 'ai';

const gateway = createGateway({
  apiKey: process.env.AI_GATEWAY_API_KEY,
});

OIDC Authentication (Vercel Deployments)

When deployed to Vercel, use OIDC tokens for automatic authentication (no API key needed):

Production/Preview: Automatic OIDC handling, no setup required.

Local Development:

Install & authenticate Vercel CLI:
```
vercel login
```
Pull OIDC token:
```
vercel env pull
```
Use
```
vercel dev
```
to start dev server (handles token refresh automatically)

Note: OIDC tokens expire after 12 hours; use

vercel dev

for automatic refresh, or run

vercel env pull

again manually.

bash

# Start dev with automatic token management
vercel dev

Basic Usage

typescript

import { generateText } from 'ai';

// Plain model string format: creator/model-name
const { text } = await generateText({
  model: 'openai/gpt-5',
  prompt: 'Explain quantum computing.',
});

console.log(text);

Gateway Instance

typescript

import { createGateway } from 'ai';

const gateway = createGateway({
  apiKey: process.env.AI_GATEWAY_API_KEY,
});

const { text } = await generateText({
  model: gateway('anthropic/claude-sonnet-4'),
  prompt: 'Write a haiku about AI.',
});

console.log(text);

Model Discovery (Dynamic)

typescript

import { gateway } from 'ai';

const availableModels = await gateway.getAvailableModels();

availableModels.models.forEach((model) => {
  console.log(`${model.id}: ${model.name}`);
  if (model.pricing) {
    console.log(`  Input: $${model.pricing.input}/token`);
    console.log(`  Output: $${model.pricing.output}/token`);
  }
});

// Use first model
const { text } = await generateText({
  model: availableModels.models[0].id,
  prompt: 'Hello world',
});

Check Credit Usage

typescript

import { gateway } from 'ai';

const credits = await gateway.getCredits();
console.log(`Balance: ${credits.balance} credits`);
console.log(`Total used: ${credits.total_used} credits`);

Streaming with Gateway

typescript

import { streamText } from 'ai';

const { textStream } = await streamText({
  model: 'openai/gpt-5',
  prompt: 'Explain serverless architecture.',
});

for await (const chunk of textStream) {
  process.stdout.write(chunk);
}

Tool Use with Gateway

typescript

import { generateText, tool } from 'ai';
import { z } from 'zod';

const weatherTool = tool({
  description: 'Get weather',
  inputSchema: z.object({ location: z.string() }),
  execute: async ({ location }) => `Sunny in ${location}`,
});

const { text } = await generateText({
  model: 'xai/grok-4', // Via Gateway
  prompt: 'What is the weather in SF?',
  tools: { getWeather: weatherTool },
});

console.log(text);

Bring Your Own Key (BYOK)

Connect your own provider credentials to Gateway for private resource access:

typescript

import { generateText } from 'ai';
import type { GatewayProviderOptions } from '@ai-sdk/gateway';

const { text } = await generateText({
  model: 'anthropic/claude-sonnet-4',
  prompt: 'Use my Anthropic account',
  providerOptions: {
    gateway: {
      byok: {
        anthropic: [{ apiKey: 'sk-ant-...' }],
      },
    } satisfies GatewayProviderOptions,
  },
});

Set up BYOK credentials in Vercel team's AI Gateway settings; no code changes needed after configuration.

Provider-Executed Tools

Some providers offer tools executed server-side (e.g., OpenAI web search). Use through Gateway by importing the provider:

typescript

import { generateText, stepCountIs } from 'ai';
import { openai } from '@ai-sdk/openai';

const result = await generateText({
  model: 'openai/gpt-5-mini',
  prompt: 'What is the Vercel AI Gateway?',
  stopWhen: stepCountIs(10),
  tools: {
    web_search: openai.tools.webSearch({}),
  },
});

console.log(result.text);

Note: Tools requiring account-specific configuration (e.g., Claude Agent Skills) may need direct provider access via BYOK.

Provider Routing & Fallback

Core Routing Options:

```
order
```
: Try providers in sequence (fallback priority)
```
only
```
: Restrict to specific providers only
```
models
```
: Fallback to alternative models if primary fails
```
user
```
: Track usage per end-user
```
tags
```
: Categorize requests for analytics
```
zeroDataRetention
```
: Only use providers with zero data retention
```
byok
```
: Request-scoped BYOK credentials

Example: Provider & Model Fallback

typescript

import { generateText } from 'ai';
import type { GatewayProviderOptions } from '@ai-sdk/gateway';

const { text } = await generateText({
  model: 'openai/gpt-4o', // Primary model
  prompt: 'Write a TypeScript haiku',
  providerOptions: {
    gateway: {
      order: ['vertex', 'anthropic'], // Try Vertex AI first, then Anthropic
      only: ['vertex', 'anthropic'], // Only allow these providers
      models: ['openai/gpt-5-nano', 'gemini-2.0-flash'], // Fallback models
      user: 'user-123',
      tags: ['code-gen', 'v2'],
    } satisfies GatewayProviderOptions,
  },
});

// Fallback sequence:
// 1. Try vertex with openai/gpt-4o
// 2. Try anthropic with openai/gpt-4o
// 3. Try vertex with openai/gpt-5-nano
// 4. Try anthropic with openai/gpt-5-nano
// etc.

Example: Usage Tracking

typescript

import { generateText } from 'ai';
import type { GatewayProviderOptions } from '@ai-sdk/gateway';

const { text } = await generateText({
  model: 'anthropic/claude-sonnet-4',
  prompt: 'Summarize this document...',
  providerOptions: {
    gateway: {
      user: 'user-abc-123', // Track per end-user
      tags: ['document-summary', 'premium-feature'],
    } satisfies GatewayProviderOptions,
  },
});

// View analytics by user and feature in Vercel Dashboard

Zero Data Retention

Route requests only to providers with zero data retention policies for sensitive data:

typescript

import { generateText } from 'ai';
import type { GatewayProviderOptions } from '@ai-sdk/gateway';

const { text } = await generateText({
  model: 'anthropic/claude-sonnet-4',
  prompt: 'Process sensitive document...',
  providerOptions: {
    gateway: {
      zeroDataRetention: true, // Enforce zero data retention
    } satisfies GatewayProviderOptions,
  },
});

When

zeroDataRetention: true

, Gateway only routes to providers that don't retain your data. No enforcement applied if omitted or

false

Key Concepts

Call Options for Agents

Dynamically configure agents at runtime:

typescript

import { ToolLoopAgent } from 'ai';
import { z } from 'zod';

const supportAgent = new ToolLoopAgent({
  model: 'groq/llama-3.3-70b-versatile',
  callOptionsSchema: z.object({
    userId: z.string(),
    accountType: z.enum(['free', 'pro', 'enterprise']),
  }),
  instructions: 'You are a support agent.',
  prepareCall: ({ options, ...settings }) => ({
    ...settings,
    instructions:
      settings.instructions +
      `\nUser: ${options.userId}, Account: ${options.accountType}`,
  }),
});

const result = await supportAgent.generate({
  prompt: 'How do I upgrade?',
  options: {
    userId: 'user-456',
    accountType: 'free',
  },
});

UI Integration with React

typescript

import { createAgentUIStreamResponse } from 'ai';
import { useChat } from '@ai-sdk/react';
import { InferAgentUIMessage } from 'ai';

// Server-side
export async function POST(request: Request) {
  const { messages } = await request.json();
  return createAgentUIStreamResponse({
    agent: weatherAgent,
    messages,
  });
}

// Client-side
type AgentMessage = InferAgentUIMessage<typeof weatherAgent>;
const { messages, sendMessage } = useChat<AgentMessage>();

Best Practices

Groq

Use
```
llama-3.3-70b-versatile
```
for balanced performance and cost.
Use
```
llama-3.1-8b-instant
```
for low-latency, lightweight tasks.
Enable
```
parallelToolCalls: true
```
(default) for faster multi-tool execution.
Use
```
serviceTier: 'flex'
```
for 10x rate limits if you can tolerate occasional failures.

Vercel AI Gateway

Always add credit card; gateway is pay-per-token.
Use
```
only
```
/
```
order
```
to control routing and costs.
Use
```
user
```
and
```
tags
```
for spend tracking and debugging.
Enable
```
zeroDataRetention
```
for sensitive data.
Check
```
gateway.getCredits()
```
regularly to monitor usage.

Agents

Use
```
ToolLoopAgent
```
as a starting point; extend only if needed.
Combine structured output with tool calling for rich responses.
Use tool approval for payment/deletion operations.
Set
```
stopWhen
```
to control loop iterations (default:
```
stepCountIs(20)
```
).

Common Patterns

RAG Agent

typescript

const ragAgent = new ToolLoopAgent({
  model: 'groq/llama-3.3-70b-versatile',
  tools: {
    searchDocs: tool({
      description: 'Search documentation',
      inputSchema: z.object({ query: z.string() }),
      execute: async ({ query }) => {
        // Call vector DB (Upstash, Pinecone, etc.)
        return { docs: [/* ... */] };
      },
    }),
  },
  instructions: 'Answer questions by searching docs.',
});

Multi-Provider with Fallback

typescript

const { text } = await generateText({
  model: 'anthropic/claude-sonnet-4',
  prompt: 'Complex task requiring reasoning',
  providerOptions: {
    gateway: {
      models: ['openai/gpt-5', 'gemini-2.0-flash'],
    },
  },
});

Cost-Optimized Selection

typescript

const isSensitive = userQuery.includes('payment');
const model = isSensitive 
  ? 'anthropic/claude-sonnet-4' 
  : 'openai/gpt-5-nano';

const { text } = await generateText({
  model,
  prompt: userQuery,
});

Timeline

AI SDK 6 Beta: Available now (pin versions)
Stable Release: End of 2025

ai-sdk-6-skills

NPX Install

Tags

SKILL.md Content

Links

Installation

What's New in AI SDK 6?

1. Agent Abstraction (New)

2. Tool Execution Approval (New)

3. Structured Output + Tool Calling (Stable)

4. Reranking Support (New)

Migration from AI SDK 5

Groq Provider (Open Weight Models)

Setup

Open Weight Models Available

Basic Llama Example

Structured Output with Llama (Groq)

Tool Use with Llama (Groq)

Reasoning Models (Groq)

Image Input with Llama (Groq Multi-Modal)

Vercel AI Gateway

What It Is

Setup

Authentication

API Key Authentication

OIDC Authentication (Vercel Deployments)

Basic Usage

Gateway Instance

Model Discovery (Dynamic)

Check Credit Usage

Streaming with Gateway

Tool Use with Gateway

Bring Your Own Key (BYOK)

Provider-Executed Tools

Provider Routing & Fallback

Example: Provider & Model Fallback

Example: Usage Tracking

Zero Data Retention

Key Concepts

Call Options for Agents

UI Integration with React

Best Practices

Groq

Vercel AI Gateway

Agents

Common Patterns

RAG Agent

Multi-Provider with Fallback

Cost-Optimized Selection

Timeline