Hands-on – implementing conversation tracking for PITS
In this practical section, we’ll use some of our newfound knowledge to further improve our personal tutoring project. Like any professional tutor, eager to teach students and answer their questions, PITS should have a proper conversational engine at its core. It should be able to understand the topic, be aware of the current context, and keep track of the entire interaction with the student. Because the learning process will probably take place through multiple sessions, PITS must be able to persist the entire conversation and resume the interaction when a new session is initiated. We’ll implement all these features in coversation_engine.py. This module is not meant to be used directly in our app architecture. Instead, it will provide three callable functions that we will later import and use in the training_UI.py module:
load_chat_store: This function is responsible for retrieving the chatbot conversation...
