AI Chatbot For Solving Mathematical Problems Using Large Language Models and Retrieval-Augmented Generation (Rag) With Custom Dataset Integration

Abstract

Mathematical problem-solving is a fundamental skill in education, and recent advancements in artificial intelligence (AI) offer innovative ways to automate this process. This paper presents an AI-powered chatbot developed using Google Vertex AI Agent Builder, designed to solve mathematical problems across various domains. By leveraging Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), the chatbot integrates a custom dataset to enhance its problem-solving capabilities, allowing it to generate accurate and contextually relevant solutions. The RAG technique enables the model to retrieve external information dynamically, improving the chatbot's ability to handle a wide range of mathematical problems. The integration of a custom dataset ensures that the model can effectively tackle specific problem types, making it adaptable to different scenarios. This work demonstrates the potential of AI-driven tools, powered by Google AI Agent Builder, to provide instant, reliable mathematical assistance, offering valuable support for students and educators alike