In this example, we use exact matching by computing the dot product similarity between the input query embedding and the image embeddings, and retrieve the top k matches. However, approximate similarity matching, using frameworks like ScaNN, Annoy, or Faiss is preferred in real-time use cases to scale with a large number of images.