The architecture of RAG for video production

Automating the process of real-world video generation, commenting, and labeling is extremely relevant in various industries, such as media, marketing, entertainment, and education. Businesses and creators are continuously seeking efficient ways to produce and manage content that can scale with growing demand. In this chapter, you will acquire practical skills that can be directly applied to meet these needs.

The goal of our RAG video production use case in this chapter is to process AI-generated videos using AI agents to create a video stock of labeled videos to identify them. The system will also dynamically generate custom descriptions by pinpointing AI-generated technical comments on specific frames within the videos that fit the user input. Figure 10.1 illustrates the AI-agent team that processes RAG for video production:

Figure 10.1: From raw videos to labeled and commented videos

We will implement AI agents for our...