AI Mental Health Therapist Chatbot using Python

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nevon software

According to the World Health Organization, there is a global shortage of health workers trained in mental health. Many mental health interventions do not reach those in need, with approximately 70% with no access to these services. Chatbots could be a scalable solution that provides an interactive means of engaging users in behavioral health interventions. Chatbots are systems that are able to converse and interact with human users using spoken, written, and visual languages. Chatbots have the potential to be useful tools for individuals with mental disorders, especially those who are reluctant to seek mental health advice due to stigmatization.

Our Mental Health Chatbot System helps users by recommending video links based on their sentiments by analyzing their patterns of communication with the chatbot. Here we have implemented the rasa framework. Rasa is a python framework that helps us to build any kind of Chatbot easily. It is based on NLU (Natural Language Processing) which offers the possibility to understand what the user wants.

Mental Health Chatbot System is based on the conversational agent that behaves like a real-time therapist who analyses the user’s emotions at every step and provides appropriate responses and feedback. Chatbots provide an effective way to communicate with a user and offer helpful emotional support in a more economical way.

In this system, there is one user module. To log in to the system, the user will need to register and then log in to their accounts. The user can start chatting with the chatbot. The system will detect the user’s sentiments based on positive, negative and neutral expressions. Based on the expression the system will recommend video links. These links will help to treat their mental health with the help of their sentiments.

The front end involves Html, CSS, and JavaScript and the back end involves Python. The framework used is Flask and the database is MySQL. The library used here is rasa.


  • It’s easy to maintain.
  • It’s user-friendly.
  • Based on a positive, negative and neutral expression user sentiments are detected.
  • Video links are provided to treat their mental health.