Abstract
: In Today’s digital age, access to legal knowledge among students is crucial for fostering a well-informed citizenry. However, comprehending the intricacies of provisions of Indian Legal Acts, especially in a complex legal system like India’s, can be daunting, even for seasoned professionals, let alone for educational purposes among children. To bridge this gap and foster legal literacy from a young age, we introduced a PDF-based Closed-domain Question-Answering (CDQA) System for Indian Legal Acts. Our system simplifies educating students about provisions of Indian Legal Acts such as RTI(Right to Education), RTE(Right to Education), Anti-Dowry Act, etc. By leveraging natural language processing(NLP) techniques and machine learning algorithms, our system, powered by LangChain, enables users to pose questions in natural language related to Indian Legal Acts. LangChain represents a groundbreaking advancement in question-answer systems, harnessing the power of cutting-edge language models to provide accurate and comprehensive responses to user queries. Developed based on state-of-the-art NLP techniques, LangChain is a versatile and highly adaptable tool that offers a versatile solution with transformative potential across diverse industries, including education, healthcare, legal research, customer support, etc.
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