LawMate : A Locally Deployable RAG System for Accessible Indian Legal Assistance Using TinyLlama and FAISS

• Author(s): Shreya Patil; Pratik Nakashe; Aditya Medhekar; Sourabh Sadake; Jyoti Bansode
• Paper ID: 1718611
• Page: 391-400
• Published Date: 04-06-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 12 June-2026
• DOI: https://doi.org/10.64388/IREV9I12-1718611

Abstract

Access to Indian legal information remains limited for non-lawyers due to complex statutory language, fragmented resources, and high consultation costs. This paper presents LawMate, a lightweight Retrieval-Augmented Generation (RAG)–based legal assistant designed to provide citation-grounded responses for everyday legal queries. The system integrates TinyLlama (1.1B parameters) with FAISS-based se-mantic retrieval over official Indian legal documents, ensuring responses are generated strictly from retrieved context to reduce hallucination. A FastAPI backend and React-based frontend enable efficient local deployment on resource-constrained devices. Experimental evaluation demonstrates high retrieval relevance, low response latency, and practical usability for citizen-facing applications. The proposed architecture provides a scalable, low-resource solution for transparent and accessible legal assistance in the Indian context.

Keywords

Legal AI, Retrieval-Augmented Generation, TinyLlama, FAISS, Indian Law, Offline Chatbot, Semantic Search, FastAPI.

Citations

IRE Journals:
Shreya Patil, Pratik Nakashe, Aditya Medhekar, Sourabh Sadake, Jyoti Bansode "LawMate : A Locally Deployable RAG System for Accessible Indian Legal Assistance Using TinyLlama and FAISS" Iconic Research And Engineering Journals Volume 9 Issue 12 2026 Page 391-400 https://doi.org/10.64388/IREV9I12-1718611

IEEE:
Shreya Patil, Pratik Nakashe, Aditya Medhekar, Sourabh Sadake, Jyoti Bansode "LawMate : A Locally Deployable RAG System for Accessible Indian Legal Assistance Using TinyLlama and FAISS" Iconic Research And Engineering Journals, vol. 9, no. 12, Jun. 2026, doi: https://doi.org/10.64388/IREV9I12-1718611

APA:
Shreya Patil, Pratik Nakashe, Aditya Medhekar, Sourabh Sadake, Jyoti Bansode (2026). LawMate : A Locally Deployable RAG System for Accessible Indian Legal Assistance Using TinyLlama and FAISS. Iconic Research And Engineering Journals, 9(12). doi: https://doi.org/10.64388/IREV9I12-1718611

MLA:
Shreya Patil, Pratik Nakashe, Aditya Medhekar, Sourabh Sadake, Jyoti Bansode "LawMate : A Locally Deployable RAG System for Accessible Indian Legal Assistance Using TinyLlama and FAISS" Iconic Research And Engineering Journals, vol. 9, no. 12, Jun. 2026. Crossref, https://doi.org/10.64388/IREV9I12-1718611

BibTeX

@article{1718611,
author = {Shreya Patil, Pratik Nakashe, Aditya Medhekar, Sourabh Sadake, Jyoti Bansode},
title = {LawMate : A Locally Deployable RAG System for Accessible Indian Legal Assistance Using TinyLlama and FAISS},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {12},
pages = {391-400},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1718611.pdf},
abstract = {Access to Indian legal information remains limited for non-lawyers due to complex statutory language, fragmented resources, and high consultation costs. This paper presents LawMate, a lightweight Retrieval-Augmented Generation (RAG)–based legal assistant designed to provide citation-grounded responses for everyday legal queries. The system integrates TinyLlama (1.1B parameters) with FAISS-based se-mantic retrieval over official Indian legal documents, ensuring responses are generated strictly from retrieved context to reduce hallucination. A FastAPI backend and React-based frontend enable efficient local deployment on resource-constrained devices. Experimental evaluation demonstrates high retrieval relevance, low response latency, and practical usability for citizen-facing applications. The proposed architecture provides a scalable, low-resource solution for transparent and accessible legal assistance in the Indian context.},
keywords = {Legal AI, Retrieval-Augmented Generation, TinyLlama, FAISS, Indian Law, Offline Chatbot, Semantic Search, FastAPI.},
month = {June}
}