Retrieval Augmented Generation Framework for the Nepali Legal Domain Question Answering

This study presents the first application of a Retrieval Augmented Generation (RAG) model for Nepali legal question answering, addressing data scarcity in low-resource languages. Using BM25 on chunked documents, the RAG pipeline achieved high precision and truthfulness, demonstrating its effectiveness in the Nepali legal domain.