diff --git a/public/sitemap.xml b/public/sitemap.xml index 32a5c50..cd88227 100644 --- a/public/sitemap.xml +++ b/public/sitemap.xml @@ -2,749 +2,749 @@ https://kagent.dev/agents - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/blog - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/community - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/concepts/agents - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/concepts/architecture - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/concepts - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/concepts/tools - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/examples/a2a-agents - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/examples/a2a-byo - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/examples/crewai-byo - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/examples/discord-a2a - 2026-01-12 + 2026-01-16 weekly 0.8 https://kagent.dev/docs/kagent/examples/documentation - 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Obtain your AWS credentials from the AWS Console. You will need the AWS Access Key ID and the AWS Secret Access Key. + +2. Create a Kubernetes secret that stores your AWS credentials in the same namespace as your agent, typically `kagent`. + + ```bash + export AWS_ACCESS_KEY_ID= + export AWS_SECRET_ACCESS_KEY= + kubectl create secret generic kagent-bedrock -n kagent --from-literal AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID --from-literal AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY + ``` + + If you are using [temporary credentials](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_use-resources.html), you will also need to set the `AWS_SESSION_TOKEN` variable in the secret. + + The above method uses Boto3 to authenticate with AWS. Alternatively, you can also use the Bedrock API key. You can create it with the [AWS Bedrock API keys guide](https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started-api-keys.html). + + ```bash + export AWS_BEARER_TOKEN_BEDROCK= + kubectl create secret generic kagent-bedrock -n kagent --from-literal AWS_BEARER_TOKEN_BEDROCK=$AWS_BEARER_TOKEN_BEDROCK + ``` + +3. Create a ModelConfig resource that uses the AWS credentials secret. + + ```yaml + apiVersion: kagent.dev/v1alpha2 + kind: ModelConfig + metadata: + name: bedrock-claude + namespace: kagent + spec: + // Choose any valid model ID from AWS Bedrock + model: anthropic.claude-3-sonnet-20240229-v1:0 + provider: Bedrock + + // This will use bearer token if it's available in the secret, otherwise the IAM credentials will be used. + apiKeySecret: kagent-bedrock + + bedrock: + region: us-east-1 + ``` + +## Alternative: Using the OpenAI Chat Completions API + You can use Amazon Bedrock models with kagent by leveraging AWS Bedrock's [OpenAI Chat Completions API](https://docs.aws.amazon.com/bedrock/latest/userguide/inference-chat-completions.html). +Note that this method might not work for all models, especially for models that are not OpenAI-compatible. -## Step 1: Prepare your AWS details +### Step 1: Prepare your AWS details 1. Follow the [AWS Bedrock API keys guide](https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started-api-keys.html) to create the API key needed for authentication. @@ -34,7 +78,7 @@ You can use Amazon Bedrock models with kagent by leveraging AWS Bedrock's [OpenA kubectl create secret generic kagent-bedrock -n kagent --from-literal AWS_API_KEY=$AWS_API_KEY ``` -## Step 2: Create the ModelConfig +### Step 2: Create the ModelConfig 1. Create a ModelConfig resource that uses the OpenAI-compatible API interface. @@ -65,4 +109,4 @@ You can use Amazon Bedrock models with kagent by leveraging AWS Bedrock's [OpenA ## Next Steps - Now that you configured your Bedrock model, you can [create or update an agent](https://kagent.dev/docs/kagent/getting-started/first-agent) to use this model configuration. +Now that you configured your Bedrock model, you can [create or update an agent](https://kagent.dev/docs/kagent/getting-started/first-agent) to use this model configuration.