Smart Chatbot for A Food Ordering Website Using Google Dialogflow

As online food services rise, adding sophisticated chatbots to food-ordering applications would increase user interaction and improve workflow. The paper outlines the construction of a chatbot built into a food-ordering website for exploring cafes and placing orders. The chatbot was constructed using Google Dialogflow ES for natural language processing and FastAPI for end-to-end communication with a MySQL relational database. The interaction between the user and the system pulled from the natural language processing allowed for entity extraction, webhook fulfilment of specific entity values, and exposed various API endpoints for interacting with the database. Testing was performed in real-time locally using ngrok. The study illustrated the capacity of AI automation to assist users, decreasing user burden, and contribute to the positive nature of user experience.