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GenAI Foundation

This starter kit deploys an enterprise-ready Customer Support Agent using Amazon Bedrock, featuring intelligent agents with RAG capabilities, knowledge bases, guardrails, and multi-sync architecture for concurrent document processing.

Deployment Instructions

Use Cases

  • Customer support agent assistant with natural language interaction
  • Knowledge base search and retrieval over internal documents
  • Document processing and analysis with RAG (Retrieval Augmented Generation)
  • Multi-modal content handling (text and images)

Capabilities

  • Bedrock Agents with custom action groups for customer support
  • Knowledge Bases with vector stores for efficient retrieval
  • Guardrails for content safety and appropriate responses
  • Multi-sync architecture for concurrent file uploads
  • KMS-encrypted S3 buckets for knowledge base data sources
  • IAM roles with least-privilege Bedrock permissions

Architecture

GenAI Foundation

Deployment

Prerequisites and Predeployment

  1. Authenticate to your target AWS account and region. Ensure the authenticated role has permissions to deploy resources via CDK.
  2. Bootstrap CDK in your target account and region.

Additional info: PREDEPLOYMENT

Configure MDAA

  1. Address all TODOs in mdaa.yaml, specifically:

    • Set organization to a globally unique name (used in S3 bucket names and all resource prefixes)
    • Set vpc_id, subnet_id_1, subnet_id_2, subnet_id_3 to your VPC/subnet IDs
    • Set llm_model to your chosen Bedrock model ID or inference profile ARN
    • Set kb_embedding_model and kb_parsing_model

  2. Address all TODOs in module configs, specifically:

    • CDK Nag suppressions in roles.yaml. Uncomment each suppression only after reviewing the associated permissions and confirming they are acceptable for your environment.

Deploy MDAA

Run the following from the starter kit directory (containing mdaa.yaml):

  1. Optionally, run npx @aws-mdaa/cli ls to understand what stacks will be deployed.

  2. Optionally, run npx @aws-mdaa/cli synth and review the produced templates.

  3. Run npx @aws-mdaa/cli deploy to deploy all modules.

Additional info: DEPLOYMENT

Next Steps

See USAGE for post-deployment instructions including model configuration, document upload, and agent testing.

Modules Deployed

Module Purpose
@aws-mdaa/roles IAM roles (data-admin, agent-execution, kb-execution, agent-lambda, kb-sync-lambda)
@aws-mdaa/datalake KMS-encrypted S3 buckets for knowledge base data sources
@aws-mdaa/bedrock-builder Bedrock Agents, Knowledge Bases, Guardrails, and Lambda action groups

Troubleshooting

  1. Access Denied when calling Bedrock: Verify the llm_model in context values is correct. For cross-region inference, use the inference profile ARN. Ensure the agent execution role has the necessary Bedrock permissions.

  2. Knowledge Base ingestion failures: Verify S3 bucket permissions and KMS key access. Check that documents are uploaded with proper encryption. Monitor CloudWatch logs for detailed error messages.

  3. Agent not responding: Ensure the agent is in "Prepared" state. Check guardrail configurations. Verify Lambda function permissions for action groups.