AWS Bedrock

Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including models hosted on AWS Bedrock.

With Portkey, you can take advantage of features like fast AI gateway access, observability, prompt management, and more, all while ensuring the secure management of your LLM API keys through a virtual key system.

Provider Slug: bedrock

Portkey SDK Integration with AWS Bedrock

Portkey provides a consistent API to interact with models from various providers. To integrate Bedrock with Portkey:

1. Install the Portkey SDK

Add the Portkey SDK to your application to interact with Anthropic's API through Portkey's gateway.

npm install --save portkey-ai

2. Initialize Portkey with the Virtual Key

Set up Portkey with your virtual key as part of the initialization configuration. You can create a virtual key for AWS Bedrock in the UI.

You can navigate to the Virtual Keys tab of your Portkey account and create a Key for AWS Bedrock that'll make it easier to make calls. You'll need the AWS Secret Access Key and AWS Access Key Id to create the virtual key.

import Portkey from 'portkey-ai'
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
    virtualKey: "VIRTUAL_KEY" // Your Bedrock Virtual Key

Using Virtual Key with AWS STS

If you're using AWS Security Token Service, you can pass your aws_session_token along with the Virtual key:

import Portkey from 'portkey-ai'
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
    virtualKey: "VIRTUAL_KEY" // Your Bedrock Virtual Key,
    aws_session_token: "<aws_session_token>"

Not using Virtual Keys?

Check out this example on how you can directly use your AWS details to make a Bedrock request through Portkey.

3. Invoke Chat Completions with AWS bedrock

Use the Portkey instance to send requests to Anthropic. You can also override the virtual key directly in the API call if needed.

const chatCompletion = await{
    messages: [{ role: 'user', content: 'Say this is a test' }],
    model: 'anthropic.claude-v2:1',
    max_tokens: 250 // Required field for Anthropic


Using Vision Models

Portkey's multimodal Gateway fully supports Bedrock's vision models anthropic.claude-3-sonnet, anthropic.claude-3-haiku, and anthropic.claude-3-opus

For more info, check out this guide:


Managing AWS Bedrock Prompts

You can manage all prompts to AWS bedrock in the Prompt Library. All the current models of Anthropic are supported and you can easily start testing different prompts.

Once you're ready with your prompt, you can use the portkey.prompts.completions.create interface to use the prompt in your application.

Making Requests without Virtual Keys

If you do not want to add your AWS details to Portkey vault, you can also directly pass them while instantiating the Portkey client.

Mapping the Bedrock Details

Node SDKPython SDKREST Headers














import Portkey from 'portkey-ai'
const portkey = new Portkey({
    apiKey: "PORTKEY_API_KEY",
    provider: "bedrock",
    awsAccessKeyId: "AWS_ACCESS_KEY_ID",
    awsSecretAccessKey: "AWS_SECRET_ACCESS_KEY",
    awsRegion: "us-east-1",
    awsSessionToken: "AWS_SESSION_TOKEN"

Supported Models

Next Steps

The complete list of features supported in the SDK are available on the link below.


You'll find more information in the relevant sections:

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