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GeetaVani: A Retrieval-Augmented LLM Framework for Contextual Dialogue from the Bhagavad Geeta

Year : 2025

Publisher : Institute of Electrical and Electronics Engineers Inc.

Source Title : ISED 2025 - 13th International Conference on Intelligent Systems and Embedded Design, Proceedings

Document Type :

Abstract

The Bhagavad Geeta, a sacred and treasured scripture in Hindu philosophy This work presents a novel Generative AI and LLM-based chatbot called GeetaVani, inspired by the teachings of the Bhagavad Geeta. It is designed to deliver contextually rich, spiritually grounded responses to user queries. By using Retrieval-Augmented Generation (RAG) framework, the system seamlessly provide precise and meaningful answers based on Geeta. The system employs Sentence-BERT to convert both Geeta verses and user queries into dense vector embeddings. These embeddings are indexed using FAISS. It enables fast and accurate retrieval of the most semantically relevant verses. The retrieved verses are then passed as contextual input to the Groq LLM API, which uses LLaMA 3 to yield response.Designed prompt ensures that the output remains faithful to the original teachings. The chatbot achieves 100% precision for the top(k)-6 results, with a Mean Average Precision of 0.89 and a gradual precision decline for broader queries beyond k is 6.