Summary

In this chapter, you explored various techniques for refining your semantic data model to improve retrieval accuracy for vector search and RAG. You learned how to improve your data model used in information retrieval and RAG. By fine-tuning embeddings, you can adjust pre-trained models to improve the accuracy and relevance of search results. With embedded metadata, you can improve the vector search quality. Finally, RAG optimization ensures that the retrieval process fetches the most relevant information.

In the next chapter, you will examine ways to address common issues in AI application development.