A Smart Legal Assistant for Indian Laws

Abstract:  This project proposes a chatbot system that integrates Retrieval-Augmented Generation (RAG) and a Knowledge Graph (KG) to address queries on Indian law. The system dynamically adapts to the complexity of user queries to optimize performance and accuracy. For straightforward questions, the RAG module retrieves relevant legal documents and generates concise answers. For complex, multi-faceted queries, the system employs a multihop reasoning approach using the knowledge graph to derive accurate and context- aware responses.To enhance accessibility and inclusivity, the chatbot supports multiple regional languages, enabling users from diverse linguistic backgrounds to interact with the system in their preferred language. This hybrid design ensures efficient computation by selectively engaging the KG only when necessary, reducing resource usage while maintaining high accuracy.The chatbot provides users with seamless access to legal insights, offering quick answers for simple queries and in- depth reasoning for complex cases. By combining the strengths of RAG and KG, this system aims to revolutionize legal assistance by improving accessibility, precision, and usability for both legal professionals and the general public, empowering users to navigate Indian law with confidence and efficiency.

The Smart Legal Advisor integrates Artificial Intelligence (AI),, Retrieval-Augmented Generation (RAG),, Knowledge Graphs (KG) to provide efficient legal assistance, By leveraging natural language processing (NLP) and multi-hop reasoning, the system delivers context-aware responses to legal queries. It supports multiple regional languages, enhancing accessibility for diverse users. The system ensures accurate legal insights by dynamically adapting to query complexity, retrieving relevant legal documents, and offering structured interpretations of Indian law. Designed for law professionals and the general public, this AI-powered legal assistant improves legal research, promotes legal awareness, and facilitates real-time guidance in a resource-efficient manner.

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