Mental Health Support Chatbot

Mental health conditions, including stress, anxiety and depression, are on the rise in workplaces and in the workplace, often as a result of today's fast-paced, high-pressure work environments. Access to quality mental healthcare suffers from social stigma, geographic barriers, and the high costs associated with treatment, resulting in many people going without proper support. Utilizing artificial intelligence and natural language processing, this study provides a comprehensive framework for a can chatbot of little cost to patients, available around the clock and created to aid in individualize mental wellness problems. The chatbot uses advanced machine learning algorithms to analyse user emotions, especially leveraging the power of DistilBERT and actions using OpenCV to detect face expression. The bot uses emotion detection and NLP skills and customize response as per emotional state of the user to ensure empathetic and situation appropriate conversation. Thus, a chatbot system that is powered by past data along with facts and AI Integration can totally change the way mental health issues are looked upon by providing users with continuous, scalable, and humanized care. Keywords: Natural Language Processing (NLP), OpenCV, Emotion Detection, AI-Powered Chatbots, DistilBERT, Text-Based Interactions, Stigma-Free Therapy, Personalized Support, Predictive Mental Health Support, and Real-Time Analytics.