TEJAS Journal of Technologies and Humanitarian Science

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Abstract:

Artificial Intelligence has rapidly transformed multiple domains, including healthcare, wellness, and fitness industries, by enabling intelligent decision-making and automation. Traditional fitness systems generally provide static and generalized workout and diet plans, which fail to consider individual user differences such as metabolism, body composition, lifestyle, and personal fitness goals. This lack of personalization often results in reduced user engagement and ineffective outcomes over time. In this research, an AI-based Fitness Coach system is proposed that leverages the capabilities of Large Language Models (LLMs) to generate personalized workout routines and dietary recommendations. The system interacts with users through a conversational interface, collects essential user data such as age, weight, height, and fitness objectives, and processes this data to generate customized plans. Technologies such as LangChain are used to manage intelligent interactions, Ollama is utilized for local model execution to ensure privacy and reduced latency, and Gradio provides a user-friendly interface for seamless interaction. Furthermore, a feedback mechanism is incorporated to continuously monitor user performance and dynamically update recommendations. The proposed system enhances personalization, improves user motivation, and provides a scalable and efficient solution for modern fitness management systems..