AI Chatbot for Enhancing Mental Health

Abstract

This project introduces a healthcare chatbot designed to improve mental well-being through mood-responsive interactions. The system integrates a Large Language Model (LLM)-powered contextual understanding, enabling adaptive and personalized responses to user input. By analyzing users' language patterns, the chatbot adapts its responses to provide context-aware, empathetic support that aligns with the user's current emotional state. Built on the Rasa framework with Natural Language Understanding (NLU) capabilities, this chatbot offers personalized, therapeutic conversations aimed at alleviating symptoms of mental health issues like stress and loneliness. This healthcare tool shows potential for enhancing user engagement and supporting mental health recovery by offering a more personalized and language-sensitive approach to care.