Summary
In this chapter, we looked at how to build intelligent applications by leveraging LangChain4j and Spring AI. We used these applications to augment the H&M transactions graph we loaded in the previous chapter, by leveraging LLM chat and embedding capabilities. Once the graph was augmented, we further enhanced the graph by leveraging vector indexes and saw how these indexes help us find similar articles or customers based on their purchases.
In the next chapter, we will step into Graph Data Science algorithms to see how we can further enhance these recommendations.
