MENTAL AND EMOTIONAL HEALTH SUPPORT SYSTEM USING CBT-BASED LLM

Abstract

Despite stigma, high costs, and resource scarcity, mental health challenges are increasingly afflicting people in all generations, but support on time, in personal and affordable manners, is still not easily reached. For this reason, Artificial Intelligence is taking on a nurturing role as a means of augmenting emotional support and scale Generative AI-Based Mental delivery of therapeutic interventions. In this project, a and Emotional Health Support System is presented, which is built upon a modular agent-based architecture to simulate a CBT inspired support. The system is built using the Gemini API and LangChain, integrating nine specialized tools such as a Retrieval Tool (Pinecone), Mood Analysis, Thought Reframing, Crisis Detection, Reflective Listening and a Web Search component (Tavily). The tool set consists of each tool as central executor that dynamically agent coordinated through a an autonomous determine user input and select the appropriate tool for instance and intent. The prompt engineering is based on modular template design with structured instructions, persona and few shot learning to guarantee tone, safety and coherence. Retrieval in relation to scientifically validated settings Augmented Generation (RAG) puts responses factual accuracy. It has a private and seamless mental health literature to increase interaction through a Streamlit interface. Crisis detection and topic filtering provide ethical safeguards to protect the user. Users and psychologists had posmve feedback on the system as a potential reliable and emotionally intelligent digital mental health companion.