Machine learning operations and LLM operations
We have seen how to create an app containing a multi-agent system. When we create a script with Python, we create an element that can run on our computer, but this is not a product. Turning a script into an app allows a user to be able to interact with our app even if they do not know how to program. Streamlit allows us to be able to run a quick prototype of our app. This is not optimal for a product, especially if it is to be used by several users. In this section, we will discuss all those operations necessary to make our model function as a product.
Machine Learning Operations (MLOps) is a set of practices and tools designed to streamline and manage the life cycle of machine learning (ML) models in production. It combines ML, DevOps, and data engineering practices to ensure the continuous integration/continuous delivery (CI/CD), monitoring, and scaling of ML systems.
Figure 10.30 – MLOps combination...
