This is a sample application showing how to use create Vector Embeddings from text using OpenAI embeddings endpoint and store and query embeddings using Qdrant Vector Database.
Vector embeddings are numerical representations of text, images, audio or video, provided by Large Language Models. In combination with a vector database like Qdrant they are a key element for recommendation systems or semantic search.