aws-samples/rag-with-amazon-opensearch-and-sagemaker

Implements retrieval-augmented generation by storing document embeddings in OpenSearch and dynamically retrieving relevant passages to augment LLM prompts, addressing token limits and improving answer accuracy. Deploys SageMaker endpoints for both text generation and embedding creation, with infrastructure-as-code (CDK) for the full stack including OpenSearch clusters and credential management. Provides a complete end-to-end workflow from data ingestion through a Streamlit frontend, leveraging LangChain for orchestration.

No commits in the last 6 months.