Conversational AI chat-bot -- Architecture overview – Towards Data Science

I will refer to the components in the above diagram, as we go through the flow. First, lets see what all things do we need to determine an appropriate response at any given moment of the conversational flow? The intent and the entities together will help to make a corresponding API call to a weather service and retrieve the results, as we will see later. Now refer to the above figure, and the box that represents the NLU component (Natural Language Understanding) helps in extracting the intent and entities from the user request. For this purpose, we need a dictionary object that can be persisted with information about the current intent, current entities, persisted information that user would have provided to bot's previous questions, bot's previous action, results of the API call (if any).