Rank products 19% better than keyword search

import { SIEClient } from '@superlinked/sie-sdk';

const client = new SIEClient(undefined, { apiKey: 'sk-sie-…' });

const query = "wayfair comforters";
const documents = [
  "···wayfair basics® comforter set···",
  "···wayfair sleep medium weight all season polyester down alternative comforter···",
  "···wayfair basics® reversible quilt set···",
  "wayfair basics single curtain rod. Curtain Hardware & Accessories",
  "wayfair basics peva shower curtain liner",
  "wayfair basics round single curtain rod. Curtain Hardware & Accessories",
];

const model = 'opensearch-project/opensearch-neural-sparse-encoding-doc-v3-gte';
const [q] = await client.encode(model, [{ text: query }], {
  outputTypes: ['sparse'],
  isQuery: true,
});
const docs = await client.encode(
  model,
  documents.map((text) => ({ text })),
  { outputTypes: ['sparse'], isQuery: false },
);
const weights = new Map<number, number>();
q!.sparse!.indices.forEach((id, i) => weights.set(Number(id), Number(q!.sparse!.values[i])));
const ranked = documents
  .map((doc, i) => {
    const d = docs[i]!.sparse!;
    let score = 0;
    d.indices.forEach((id, j) => {
      score += (weights.get(Number(id)) ?? 0) * Number(d.values[j]);
    });
    return { doc, score };
  })
  .sort((a, b) => b.score - a.score);
console.log(ranked);

# Encode the query with is_query, then the listings; rank by sparse dot product.
curl https://api.superlinked.com/v1/encode/opensearch-project%2Fopensearch-neural-sparse-encoding-doc-v3-gte \
  -H "Authorization: Bearer sk-sie-…" \
  -H "Content-Type: application/json" \
  -d "{\"items\":[{\"text\":\"wayfair comforters\"}],\"params\":{\"output_types\":[\"sparse\"],\"options\":{\"is_query\":true}}}" \
  -H "Accept: application/json" -o query.json

curl https://api.superlinked.com/v1/encode/opensearch-project%2Fopensearch-neural-sparse-encoding-doc-v3-gte \
  -H "Authorization: Bearer sk-sie-…" \
  -H "Content-Type: application/json" \
  -d "{\"items\":[{\"text\":\"···wayfair basics® comforter set···\"},{\"text\":\"···wayfair sleep medium weight all season polyester down alternative comforter···\"},{\"text\":\"···wayfair basics® reversible quilt set···\"},{\"text\":\"wayfair basics single curtain rod. Curtain Hardware & Accessories\"},{\"text\":\"wayfair basics peva shower curtain liner\"},{\"text\":\"wayfair basics round single curtain rod. Curtain Hardware & Accessories\"}],\"params\":{\"output_types\":[\"sparse\"],\"options\":{\"is_query\":false}}}" \
  -H "Accept: application/json" -o listings.json

jq --slurpfile q query.json '($q[0].items[0].sparse | [.indices, .values] | transpose | map({key: (.[0] | tostring), value: .[1]}) | from_entries) as $w | [.items | to_entries[] | {listing: .key, score: ([.value.sparse.indices, .value.sparse.values] | transpose | map(($w[.[0] | tostring] // 0) * .[1]) | add // 0)}] | sort_by(-.score)' listings.json