Amazon Bedrock#

You can use Amazon Bedrock models with kagent in two ways: the native Bedrock provider (recommended) or the OpenAI-compatible API interface.

Option 1: Native Bedrock provider#

The native Bedrock provider uses AWS IAM credentials and the Bedrock API directly. Use this option when you want the simplest configuration and full Bedrock feature support.

Step 1: Prepare your AWS credentials#

1. Create an IAM user or role with permissions for Bedrock. You need at least bedrock:InvokeModel for the models you use. For more information, see the AWS Bedrock model access docs.

2. Choose the AWS region and Bedrock model. Refer to the AWS Bedrock supported models documentation.

   • Example regions: us-east-1 or us-west-2
   • Example model IDs: us.anthropic.claude-sonnet-4-20250514-v1:0 or amazon.titan-text-express-v1

3. Create a Kubernetes secret with your AWS credentials in the same namespace as your agent, typically kagent:

   kubectl create secret generic bedrock-credentials -n kagent \
     --from-literal=AWS_ACCESS_KEY_ID=<your-access-key> \
     --from-literal=AWS_SECRET_ACCESS_KEY=<your-secret-key>

Step 2: Create the ModelConfig#

kubectl apply -f - <<EOF
apiVersion: kagent.dev/v1alpha2
kind: ModelConfig
metadata:
  name: bedrock-native
  namespace: kagent
spec:
  provider: Bedrock
  model: us.anthropic.claude-sonnet-4-20250514-v1:0
  apiKeySecret: bedrock-credentials
  bedrock:
    region: us-east-1
EOF

Option 2: OpenAI-compatible API#

You can also use Bedrock models via the OpenAI Chat Completions API. This option is useful when you need compatibility with the OpenAI API format or when using Bedrock's inference profiles.

Step 1: Prepare your AWS details#

1. Follow the AWS Bedrock API keys guide to create the API key needed for authentication.

2. Choose the AWS region and Bedrock model. Refer to the AWS Bedrock supported models documentation.

   • Example regions: us-west-2 or us-east-1
   • Example model IDs: amazon.titan-text-express-v1 or openai.gpt-oss-20b-1:0. Ensure your AWS account has access to the chosen model. Some models, like Anthropic models, may require additional access controls. For more information, see the AWS Bedrock model access docs.

3. Save your AWS API key as an environment variable.

   export AWS_API_KEY=<your-aws-api-key>

4. Create a Kubernetes secret that stores your AWS API key in the same namespace as your agent, typically kagent.

   kubectl create secret generic kagent-bedrock -n kagent --from-literal AWS_API_KEY=$AWS_API_KEY

Step 2: Create the ModelConfig#

kubectl apply -f - <<EOF
apiVersion: kagent.dev/v1alpha2
kind: ModelConfig
metadata:
  name: bedrock-config
  namespace: kagent
spec:
  apiKeySecret: kagent-bedrock
  apiKeySecretKey: AWS_API_KEY
  model: amazon.titan-text-express-v1
  provider: OpenAI
  openAI:
    baseUrl: "https://bedrock-runtime.us-west-2.amazonaws.com/openai/v1"
EOF

Next steps#

Now that you configured your Bedrock model, you can create or update an agent to use this model configuration.