A lightweight, graph-based retrieval-augmented generation (RAG) framework that uses a dual-layer architecture combining knowledge graphs and vector embeddings to deliver efficient indexing, low-cost incremental updates, and high-quality contextual retrieval.
A template for building AI chatbots and document management systems using Retrieval-Augmented Generation (RAG), vector search, and FastAPI, designed for deployment on Kubernetes.
