var songs = client.collections.use("Songs");

// One concept
songs.query.nearText("rain", opt -> opt.distance(.1f));

// Multiple concepts
songs.query.nearText(List.of("black", "yellow"),
  opt -> opt
    .moveTo(.2f, to -> to.concepts("money", "party"))
    .moveAway(.5f, away -> away.uuids("0000-000-000-000000")));

// Group by works as expected
songs.query.nearText("weather", new GroupBy("month", 12, 5));

Vectorizer.text2vecContextionary(opt -> opt.vectorizeCollectionName(true));

Vectorizer.text2vecWeaviate(opt -> opt.dimensions(384));

Vectorizer.multi2vecClip(opt -> opt.imageFields("avatar").textFields("bio", "hobbies"));

Vectorizer.img2vecNeural(opt -> opt.imageFields("avatar"));

// Create BLOB property
client.collections.create("Creators",
  collection -> collection.properties(
    Property.text("name"),
    Property.integer("followers"),
    Property.blob("avatar")));

var creators = client.collections.use("Creators");

// Insert data: nothing surprising here yet (planning to add some DX-boosters in the future)
creators.data.insert(Map.of(
  "name", "johndoe",
  "followers", 100_243,
  "avatar", "<base64-encoded-image>"))

// Query lookalikes
creators.query.nearImage("<base64-encoded-image>", opt -> opt.limit(6));