use rbert::*;
#[tokio::main]
async fn main() -> anyhow::Result<()> {
let bert = Bert::builder().build().await?;
let sentences = [
"Kalosm can be used to build local AI applications",
"With private LLMs data never leaves your computer",
"The quick brown fox jumps over the lazy dog",
];
let embeddings = bert.embed_batch(sentences).await?;
println!("embeddings {:?}", embeddings);
let mut similarities = vec![];
let n_sentences = sentences.len();
for (i, e_i) in embeddings.iter().enumerate() {
for j in (i + 1)..n_sentences {
let e_j = embeddings.get(j).unwrap();
let cosine_similarity = e_j.cosine_similarity(e_i);
similarities.push((cosine_similarity, i, j))
}
}
similarities.sort_by(|u, v| v.0.total_cmp(&u.0));
for &(score, i, j) in similarities.iter() {
println!("score: {score:.2} '{}' '{}'", sentences[i], sentences[j])
}
Ok(())
}