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Abstract The management of a mental health of a person has been made possible in recent years by a variety of virtual assistants. This paper uses a Rule-based Chatbot to provide a quick description of a mental state of a human. An AI-powered computer programme known as a Chatbot can mimic human interaction via voice commands, text dialogues, or a combination of the two. This AI function, also referred to as a Rule-based Chatbot, can be included in and used with well-known messaging platforms. The natural language toolkit is used in the implementation of this Chatbot. Natural language processing (NLP), a branch of AI, is used by Chatbot powered by AI to improve the user experience. These NLP-based Chatbot, also known as virtual agents or intelligent virtual assistants, support human agents by managing time-consuming and repetitive exchanges. Human agents can now concentrate on instances that require their knowledge because they are more complex. NLP-based Chatbot are intelligent in that they can understand speech patterns, text structures, and language semantics. Because of this, they can analyze and derive meaning from massive amounts of unstructured data. A Chatbot has the capacity to perceive small differences in different languages which is improved by cross-linguistic comprehension of morphemes of Natural Language Processing(NLP). In addition, NLP gives Chatbot the capacity to comprehend unused words, adjust to changing abbreviations, and identify emotions through sentiment analysis, simulating human-like comprehension. This model depicts a Chatbot that responds to user inquiries in a brief and straightforward manner. Although conversational AI is frequently associated with Chatbot, not all Chatbot use AI. In general, rules-based Chatbot are used to describe Chatbot that do not use AI. These Chatbot direct users towards particular behaviours using established rules and decision trees. These scripts and rules are predetermined, and any changes call for manual action from the organization. One of the early alternative therapies explored was cognitive behavioural therapy. The user must, however, attend face-to-face counseling, which could last nine to twelve years. The first virtual assistant designed in 1950 to read a person's mental state was the Turing test. The main goal of this proposed system is to overcome the difficulties in determining the appropriate responses to the user's inquiries. Performance metrics such as Similarity Bow and Term frequency-inverse document frequency (TF-IDF) score is used to evaluate the similarity between the exact answer and predicted answer.

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