Semantic search using Elasticsearch and OpenAI (Part 11)
Next steps
Success! Now you know how to use Elasticsearch as a vector database to store embeddings, encode queries by calling the OpenAI embeddings endpoint, and run semantic search.

Play around with different queries, and if you want to try with your own data, you can experiment with different embedding models.

ℹ️ Check out our other notebook Retrieval augmented generation using Elasticsearch and OpenAI. That notebook builds on this example to demonstrate how to use Elasticsearch together with the OpenAI chat completions API for retrieval augmented generation (RAG).