IntroductionThe Indian Lok Sabha generates a continuously expanding corpus of legislative records, predominantly archived as unstructured PDF files. Effective public access remains limited due to the shortcomings of keyword-based retrieval systems and the hallucination risks of general-purpose Large Language Models (LLMs).MethodsThis paper presents a domain-specific, resource-efficient Retrieval-Augmented Generation (RAG) framework employing DistilGPT-2 (82M parameters) as the generative model,