Building a multimodal modular RAG program for drone technology

In the following sections, we will build a multimodal modular RAG-driven generative system from scratch in Python, step by step. We will implement:

• LlamaIndex-managed OpenAI LLMs to process and understand text about drones
• Deep Lake multimodal datasets containing images and labels of drone images taken
• Functions to display images and identify objects within them using bounding boxes
• A system that can answer questions about drone technology using both text and images
• Performance metrics aimed at measuring the accuracy of the modular multimodal responses, including image analysis with GPT-4o

Also, make sure you have created the LLM dataset in Chapter 2 since we will be loading it in this section. However, you can read this chapter without running the notebook since it is self-contained with code and explanations. Now, let’s get to work!

Open the Multimodal_Modular_RAG_Drones...