It becomes easier for the users to make chatbots using the ChatterBot library with more accurate responses. A newly initialized Chatterbot instance starts off with no knowledge of how to communicate. To allow it to properly respond to user inputs, the instance needs to be trained to understand how conversations flow. Since Chatterbot relies on machine learning at its backend, it can very easily be taught conversations by providing it with datasets of conversations. You can use if-else control statements that allow you to build a simple rule-based Python Chatbot. You can interact with the Chatbot you have created by running the application through the interface. NLTK is one such…