O. I. OMOIFO

The increasing complexity of modern programming environments has created a growing need for intelligent, real-time support systems capable of assisting students and developers in understanding, writing, and debugging code. This project presents the design and implementation of an AI-powered chatbot web application that leverages Large Language Model (LLM)- based Natural Language Processing (NLP) and Remote Code Execution APIs to address programming queries interactively. The system integrates Google’s Gemini API for natural language understanding and JDoodle API for live code execution within a secure, microservicebased architecture. The chatbot provides conversational assistance, real-time code validation, debugging support, and algorithmic explanations through a responsive web interface built with React, TypeScript, Tailwind CSS, and Vite. The backend is implemented using Node.js, Express.js, and MongoDB, with modular microservices for authentication, chatbot intelligence, and code execution, all orchestrated through an API Gateway. This architecture ensures scalability, maintainability, and independent service deployment, while also improving accessibility for users in resource-constrained environments. The system demonstrates how combining LLMs with execution APIs can create a more reliable and contextaware programming assistant than traditional static or rule-based systems. The outcome of this project is a robust, user-friendly, and intelligent chatbot that enhances learning efficiency, developer productivity, and accessibility to programming support, particularly for students in developing regions. It contributes to ongoing research in AI-driven education, NLP, and intelligent tutoring systems, offering a sustainable model for future AIintegrated learning platforms.

The increasing complexity of modern programming environments has created a growing need for intelligent, real-time support systems capable of assisting students and developers in understanding, writing, and debugging code. This project presents the design and implementation of an AI-powered chatbot web application that leverages Large Language Model (LLM)-based Natural Language Processing (NLP) and Remote Code Execution APIs to address programming queries interactively. The system integrates Google’s Gemini API for natural language understanding and JDoodle API for live code execution within a secure, microservicebased architecture. The chatbot provides conversational assistance, real-time code validation, debugging support, and algorithmic explanations through a responsive web interface built with React, TypeScript, Tailwind CSS, and Vite. The backend is implemented using Node.js, Express.js, and MongoDB, with modular microservices for authentication, chatbot intelligence, and code execution, all orchestrated through an API Gateway.This architecture ensures scalability, maintainability, and independent service deployment, while also improving accessibility for users in resource-constrained environments. The system demonstrates how combining LLMs with execution APIs can create a more reliable and contextaware programming assistant than traditional static or rule-based systems. The outcome of this project is a robust, user-friendly, and intelligent chatbot that enhances learning efficiency, developer productivity, and accessibility to programming support, particularly for students in developing regions. It contributes to ongoing research in AI-driven education, NLP, and intelligent tutoring systems, offering a sustainable model for future AIintegrated learning platforms.