Abstract: Mental health issues like anxiety and depression and even stress have become major issues in society and contribute to a lowering standard of living, productivity levels have decreased, and individuals are becoming more aware of their struggles. Unfortunately, many cannot access professional therapy due to stigma, cost, and a lack of trained professionals. This research seeks to outline the design and development of an AI based Mental Health Chatbot using Python, Flask and Natural Language Processing (NLP) to aid individuals in mental health support 24/7 in a confidential, professional and unbiased manner.

The system encapsulates a classifier that was trained on a larger dataset which includes many intents related to both mental and physical health, which enables the chatbot to discover stress, anxiety, and depression but also larger physical health challenges like a fever or cold. It comes with user authentication, chat history, carries on conversation, real time prediction accuracy. The experimental results showcase ~92% accuracy with intent classification, ensuring the responses were empathetic and trustworthy.

Keywords: Mental health chatbot, natural language processing, Flask, python, supervised learning, health informatics, AI-based therapy, intent classification.

Downloads: | DOI: 10.17148/IARJSET.2025.12833