How does Hibernate 7 support vector data types for AI/ML applications?

import org.hibernate.annotations.Array;
import org.hibernate.type.SqlTypes;

@Entity
public class Document {
    @Id @GeneratedValue private Long id;
    private String content;

    // Float32 vector (e.g. OpenAI text-embedding-3 embeddings):
    @JdbcTypeCode(SqlTypes.VECTOR)
    @Array(length=1536)  // number of dimensions
    private float[] embedding;

    // Binary vector (Hibernate 7.2+):
    @JdbcTypeCode(SqlTypes.VECTOR_BINARY)
    @Array(length=24)
    private byte[] binaryVector;

    // Half-precision float16 (Hibernate 7.2+):
    @JdbcTypeCode(SqlTypes.VECTOR_FLOAT16)
    @Array(length=1536)
    private float[] halfPrecisionEmbedding;
}

// Vector similarity search (pgvector required):
List<Object[]> similar = session
    .createNativeQuery(
        "SELECT d.id, d.content, d.embedding <=> :queryVec AS distance "
        + "FROM document d ORDER BY distance ASC LIMIT 10", Object[].class)
    .setParameter("queryVec", queryEmbedding)
    .getResultList();

// HQL distance functions (Hibernate 7.1+):
List<Document> results = session
    .createQuery("FROM Document d ORDER BY cosine_distance(d.embedding, :vec) ASC", Document.class)
    .setParameter("vec", queryEmbedding).setMaxResults(10).getResultList();