/rag-implementation

PurposeBuild Retrieval-Augmented Generation (RAG) systems for LLM apps using vector databases and semantic search. Provides vector DB selection, embedding strategies, retrieval (dense/sparse/hybrid), reranking, and LangGraph code. Enables grounded, citation-backed answers that reduce hallucinations and connect LLMs to external knowledge.