TNGov-GPT: Pioneering Conversational AI Chat through Tamil Nadu Government Insights and Transformer Innovations

Abstract

In this study, we introduce an innovative chatbot that utilizes Large Language Models (LLMs) and Generative Artificial Intelligence (AI) techniques. The chatbot undergoes training with a carefully curated dataset extracted from official Indian government websites. This dataset covers a wide array of information, enabling the transformer model to generate responses that are contextually relevant to user queries. Our methodology involves the extraction of data, its preprocessing, and the training of a transformer-based model to handle question-and-answer interactions. The paper explores the nuances of the dataset, highlighting its distinct characteristics and challenges. We delve into the model architecture, providing a detailed understanding of the implemented LLMs and Generative AI. The results from experiments demonstrate the efficacy of the proposed chatbot in delivering precise and informative responses. This study contributes to the evolving field of conversational AI by utilizing publicly accessible government data for training, expanding the potential applications of such models. In the discussion section, we critically analyze the outcomes, addressing both the strengths and limitations of our approach. Comparative insights with existing methodologies serve to validate the effectiveness of the developed chatbot. As a pioneering endeavor, this research not only showcases the capabilities of transformer models in handling government data but also suggests potential avenues for future enhancements and applications in various domains.

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