AI therapist App - your personal mental health companion

Abstract

Mental health challenges affect millions globally, yet access to quality care remains limited due to cost, stigma, and scarcity of trained professionals. This research addresses this gap by developing an AI Therapist Web app using Retrieval Augmented Generation (RAG) models trained on validated medical literature. The system provides accessible, evidence-based mental health support while emphasizing responsible AI implementation. Our methodology combined software development using Ruby on Rails, machine learning techniques, and user-centered design principles. We leveraged Google’s Gemini 2.0 as our foundation model for the RAG implementation, enhancing its capabilities with domain specific knowledge retrieval. This research contributes to the growing field of AI in healthcare while addressing critical accessibility challenges in mental health support. The developed system serves as a complementary tool to traditional therapy, potentially reducing barriers to care for underserved populations.