Built an Customized LLM with RAG for Singaporean laws and acts.
This open-source project slashes legal research time by citing specific acts and page numbers.
Deep Dive
A developer created 'Explore Singapore,' an open-source RAG system that queries 594 government PDFs containing 33,000 pages of laws and historical archives. It uses FAISS and BGE-M3 embeddings to provide accurate, cited answers, like citing the Air Navigation Act for drone laws, instead of generic LLM advice. The pipeline chunks text, retrieves the top relevant document, and synthesizes a response with citations via a Flask/React frontend.
Why It Matters
It demonstrates a practical, open-source blueprint for building accurate, domain-specific AI assistants that reduce hallucinations in critical fields like law.