Vercel AI SDK

Name: Strands Agents SDK
Author: Strands Agents

The Vercel AI SDK is a TypeScript toolkit for building AI-powered applications. It defines a Language Model Specification that standardizes how applications interact with LLMs across providers. The Strands Agents SDK includes a VercelModel adapter that wraps any Language Model Specification v3 (LanguageModelV3) provider for use as a Strands model provider.

This means you can bring models from the entire Vercel AI SDK ecosystem - including @ai-sdk/openai, @ai-sdk/anthropic, @ai-sdk/amazon-bedrock, @ai-sdk/google, and many more - directly into Strands agents.

Installation

Install the Strands SDK along with the Vercel AI SDK provider package for the model you want to use:

# OpenAI
npm install @strands-agents/sdk @ai-sdk/openai

# Amazon Bedrock
npm install @strands-agents/sdk @ai-sdk/amazon-bedrock

# Anthropic
npm install @strands-agents/sdk @ai-sdk/anthropic

# Google Generative AI
npm install @strands-agents/sdk @ai-sdk/google

The @ai-sdk/provider package (which defines the LanguageModelV3 interface) is listed as an optional peer dependency of @strands-agents/sdk and will be installed automatically with any @ai-sdk/* provider.

Usage

Create a LanguageModelV3 instance from any Vercel provider and wrap it with VercelModel:

OpenAI

import { Agent } from '@strands-agents/sdk'
import { VercelModel } from '@strands-agents/sdk/vercel'
import { openai } from '@ai-sdk/openai'

const agent = new Agent({
  model: new VercelModel(openai('gpt-4o')),
})

const result = await agent.invoke('Hello!')
console.log(result)

Amazon Bedrock

import { Agent } from '@strands-agents/sdk'
import { VercelModel } from '@strands-agents/sdk/vercel'
import { bedrock } from '@ai-sdk/amazon-bedrock'

const agent = new Agent({
  model: new VercelModel(bedrock('us.anthropic.claude-sonnet-4-20250514-v1:0')),
})

const result = await agent.invoke('Hello!')
console.log(result)

Anthropic

import { Agent } from '@strands-agents/sdk'
import { VercelModel } from '@strands-agents/sdk/vercel'
import { anthropic } from '@ai-sdk/anthropic'

const agent = new Agent({
  model: new VercelModel(anthropic('claude-sonnet-4-20250514')),
})

const result = await agent.invoke('Hello!')
console.log(result)

Google Generative AI

import { Agent } from '@strands-agents/sdk'
import { VercelModel } from '@strands-agents/sdk/vercel'
import { google } from '@ai-sdk/google'

const agent = new Agent({
  model: new VercelModel(google('gemini-2.5-flash')),
})

const result = await agent.invoke('Hello!')
console.log(result)

Configuration

The second argument to VercelModel accepts configuration options. These include all LanguageModelV3CallOptions settings (temperature, topP, topK, penalties, stop sequences, seed, etc.) plus the base Strands model config fields.

const model = new VercelModel(openai('gpt-4o'), {
  maxTokens: 1000,
  temperature: 0.7,
  topP: 0.9,
})

const agent = new Agent({ model })
const result = await agent.invoke('Write a short poem')
console.log(result)

Parameter	Description	Example
`modelId`	Override the model ID (defaults to the provider’s model ID)	`'gpt-4o'`
`maxTokens`	Maximum tokens to generate	`1000`
`temperature`	Controls randomness	`0.7`
`topP`	Nucleus sampling	`0.9`
`topK`	Top-k sampling	`40`
`presencePenalty`	Encourages new topics	`0.5`
`frequencyPenalty`	Reduces repetition	`0.5`
`stopSequences`	Custom stop sequences	`['END']`
`seed`	Deterministic generation	`42`

When new fields are added to the Language Model Specification, they become available in the config automatically.

Streaming

The adapter supports streaming text, reasoning content, and tool use:

const agent = new Agent({
  model: new VercelModel(openai('gpt-4o')),
})

for await (const event of agent.stream('Tell me a story')) {
  if (event.type === 'modelContentBlockDeltaEvent' && event.delta.type === 'textDelta') {
    process.stdout.write(event.delta.text)
  }
}

Supported features

The VercelModel adapter handles:

Streaming text, reasoning, and tool use (both incremental and complete tool call events)
Message formatting: text, images, documents, video, tool use/results, and reasoning blocks
Tool specification and tool choice mapping
Usage and token tracking including cache read/write tokens
Error classification: maps provider errors to ModelThrottledError, ContextWindowOverflowError, and ModelError

Compatible providers

Any package that implements the LanguageModelV3 interface works with VercelModel. This includes all official Vercel AI SDK providers and community providers:

Provider	Package
OpenAI	`@ai-sdk/openai`
Amazon Bedrock	`@ai-sdk/amazon-bedrock`
Anthropic	`@ai-sdk/anthropic`
Google Generative AI	`@ai-sdk/google`
Google Vertex	`@ai-sdk/google-vertex`
Azure OpenAI	`@ai-sdk/azure`
Mistral	`@ai-sdk/mistral`
Cohere	`@ai-sdk/cohere`
xAI Grok	`@ai-sdk/xai`
DeepSeek	`@ai-sdk/deepseek`
Groq	`@ai-sdk/groq`

See the Vercel AI SDK providers page for the full list.

Troubleshooting

Missing peer dependency

If you see warnings about @ai-sdk/provider, install it explicitly:

npm install @ai-sdk/provider

Authentication errors

Authentication is handled by the underlying Vercel provider package. Refer to the specific provider’s documentation for credential setup - for example, @ai-sdk/openai reads OPENAI_API_KEY from the environment, and @ai-sdk/amazon-bedrock uses the standard AWS credential chain.