// Generated by orrery. Edit the diagram spec and re-render instead of editing this file. import { type SVGProps, useId } from "react"; export default function RetrievalAugmentedGenerationOnAWS(props: SVGProps) { const uid = useId().replace(/[^A-Za-z0-9_-]/g, ""); return ( Retrieval augmented generation on AWS Retrieval augmented generation on AWS. 10 components in 4 groups. Connections: Users to Amazon Cognito (sign in); Users to Amazon API Gateway (question); Amazon Cognito to Amazon API Gateway (verify token); Amazon API Gateway to RAG agent; RAG agent to Amazon Bedrock (prompt and context); RAG agent to Amazon Bedrock (embed question); RAG agent to Vector index (retrieve); Documents to Ingestion function (ObjectCreated); Ingestion function to Amazon Bedrock (chunks); Ingestion function to Vector index (index); RAG agent to Amazon CloudWatch; Ingestion function to Amazon CloudWatch. RETRIEVAL AUGMENTED GENERATION ON AWS Documents are chunked and embedded into OpenSearch Serverless; an AgentCore agent retrieves context and answers with a Bedrock model SIGN IN QUESTION QUESTION VERIFY TOKEN PROMPT AND CONTEXT PROMPT AND CONTEXT EMBED QUESTION RETRIEVE OBJECTCREATED CHUNKS INDEX AWS CLOUD US-EAST-1 QUERY INGESTION USERS AMAZON COGNITO User pool AMAZON API GATEWAY RAG AGENT Amazon Bedrock AgentCore Runtime AMAZON BEDROCK Text generation model DOCUMENTS Amazon S3 bucket INGESTION FUNCTION Chunk and embed AMAZON BEDROCK Titan Text Embeddings V2 VECTOR INDEX Amazon OpenSearch Serverless AMAZON CLOUDWATCH Logs and traces REQUESTS AND DATA AUTHENTICATION TELEMETRY ); }