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.

NodeJS

npm install --save portkey-ai

Python

pip install portkey-ai

2. Initialize Portkey with the Virtual Key

To integrate AWS Bedrock with Portkey, you need the AWS Secret Access Key, AWS Access Key Id, and AWS Region with which you can create your Virtual key on Portkey.

Here's a guide on where to find your AWS credentials on AWS.

NodeJS SDK

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
})

Python SDK

from portkey_ai import Portkey

portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY"   # Replace with your virtual key for Bedrock
)

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:

NodeJS

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>"
})

Python

from portkey_ai import Portkey

portkey = Portkey(
    api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY"   # Replace with your virtual key for Bedrock,
    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.

NodeJS SDK

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

console.log(chatCompletion.choices);

Python SDK

completion = portkey.chat.completions.create(
    messages= [{ "role": 'user', "content": 'Say this is a test' }],
    model= 'anthropic.claude-v2:1',
    max_tokens=250 # Required field for Anthropic
)
    
print(completion.choices)

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:

Vision

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 SDK	Python SDK	REST Headers
awsAccessKeyId	aws_access_key_id	x-portkey-aws-session-token
awsSecretAccessKey	aws_secret_access_key	x-portkey-aws-secret-access-key
awsRegion	aws_region	x-portkey-aws-region
awsSessionToken	aws_session_token	x-portkey-aws-session-token

Example

NodeJS

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"
})

Python

from portkey_ai import Portkey

client = Portkey(
    api_key="PORTKEY_API_KEY",
    provider="bedrock",
    aws_access_key_id="<aws_acces_key_id>",
    aws_secret_access_key="<aws_secret_acces_key>",
    aws_region="us-east-1",
    aws_session_token="<aws_session_token>"
)

REST API

curl https://api.portkey.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-provider: bedrock" \
  -H "x-portkey-aws-session-token: $AWS_SESSION_TOKEN" \
  -H "x-portkey-aws-secret-access-key: $AWS_SECRET_ACCESS_KEY" \
  -H "x-portkey-aws-region: $AWS_REGION" \
  -H "x-portkey-aws-session-token: $AWS_TOKEN" \
  -d '{
    "model": "gpt-4o",
    "messages": [{"role": "user","content": "Hello!"}]
  }'

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Supported Models

Amazon Bedrock model IDs - Amazon Bedrock

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How to Find Your AWS Credentials

Navigate here in the AWS Management Console to obtain your AWS Access Key ID and AWS Secret Access Key.

• In the console, you'll find the 'Access keys' section. Click on 'Create access key'.

• Copy the Secret Access Key once it is generated, and you can view the Access Key ID along with it.

• On the same page under the 'Access keys' section, where you created your Secret Access key, you will also find your Access Key ID.

• And lastly, get Your AWS Region from the Home Page of AWS Bedrock as shown in the image below.

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Next Steps

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

SDK

You'll find more information in the relevant sections:

1. Add metadata to your requests

2. Add gateway configs to your Bedrock requests

3. Tracing Bedrock requests

4. Setup a fallback from OpenAI to Beckrock APIs