retrieval-augmented-generation

Retrieval-augmented generation for a TypeScript/NestJS backend - ingestion pipelines, document parsing, chunking strategy, embeddings and model versioning, vector store choice, hybrid keyword plus vector search, reranking, metadata filtering, query rewriting, citations and grounded answers, freshness and re-indexing, access control on retrieved documents, and evaluating retrieval and answer quality. Load when building or tuning search over private documents, adding a knowledge base to a chat or agent, debugging irrelevant or ungrounded answers, or designing an indexing pipeline.