Year: 2025
Type: article
Abstract: - This study introduces a Programmable NLU-Powered 3-in-1 ChatBot, a conversational AI framework designed to enhance response precision and contextual relevance through the integration of multiple specialized language models. The system comprises three distinct large language models (LLMs), each optimized for specific interaction domains: general conversation, problem-solving, and technical inquiry. A fourth LLM operates as a natural language understanding (NLU) controller, responsible for analyzing user input and determining the most appropriate model to handle the query. Developed using a modular architecture, the chatbot supports real-time interaction, session-level context retention, and adjustable response creativity. By employing a model selection mechanism guided by semantic analysis, the framework ensures that responses are not only contextually aligned but also domain-appropriate. This study highlights the effectiveness of combining specialized LLMs with an intelligent routing layer to improve the adaptability and accuracy of multi-domain conversational systems. The study represents a significant step toward redefining virtual assistant capabilities by offering an engaging, multi-modal interface that enhances user interaction and information retention. Key Words: Natural Language Processing (NLP), Multi-Model ChatBot, Large Language Models (LLMs), Domain-Specific Language Models, Conversational AI.
DOI: 10.55041/ijsrem49760
Author: Ramesh Alladi
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4411149950