Paper Contents
Abstract
abstract This project introduces a legal chatbot powered by AI to assist users with understanding Indian Penal Code (IPC) sections and querying the contents of uploaded legal documents. The system leverages large language models with natural language processing to interpret IPC laws, explain legal terminology, and provide contextual answers based on user-uploaded case files or legal texts. The backend is built using Fast API, and the frontend is designed with Tailwind CSS for seamless user interaction. The chatbot accepts natural language questions and PDFWord document uploads, offering dynamic responses aligned with Indian legal frameworks. 1. INTRODUCTION The growing need for accessible and reliable legal guidance has driven the exploration of artificial intelligence (AI) in the field of legal services. Many individuals, especially those residing in rural or underserved areas, face significant barriers in consulting legal professionals due to geographical limitations, financial constraints, or lack of immediate legal resources. Early understanding of legal implications and timely advice are essential to safeguard rights, reduce anxiety, and guide citizens through complex judicial processes.Traditional legal consultations often require in-person meetings, which can be time-consuming, costly, and dependent on the availability of legal experts. However, advancements in AIparticularly in natural language processing (NLP) and multimodal learninghave enabled the development of intelligent systems capable of simulating legal interactions, interpreting legal documents, and explaining statutory provisions. Vision-language models (VLMs), which combine image analysis with text understanding, are especially valuable for applications that require interpreting both legal texts and document images.This study introduces an AI-powered legal chatbot designed to assist users in understanding the Indian Penal Code (IPC) and related legal documents. The system integrates two LLaMA-based vision-language models (LLaVA) to analyze uploaded legal documents and provide intelligent responses to user queries through natural language dialogue. The backend is built using FastAPI, while the frontend utilizes Tailwind CSS to offer a seamless and interactive user experience. By supporting multimodal inputs, the system aims to democratize access to legal information, particularly around IPC sections, and empower individuals to make more informed legal decisions.
Copyright
Copyright © 2025 Ramya B N1. This is an open access article distributed under the Creative Commons Attribution License.
