This research introduces a novel OnRL-RAG system that combines Retrieval-Augmented Generation with personalization techniques to create more effective mental health dialogue systems.

• Overcomes LLM knowledge limitations by retrieving relevant, up-to-date information
• Adapts communication style to individual user preferences and needs
• Delivers personalized mental health support for issues like stress, anxiety, and depression
• Demonstrates how AI can be tailored to provide more empathetic and effective healthcare interactions

This advancement matters for healthcare as it shows how AI systems can be optimized to provide more personalized mental health support, potentially increasing accessibility and effectiveness of digital mental health interventions.

OnRL-RAG: Real-Time Personalized Mental Health Dialogue System