In-memory semantic search; load it up with valtown KV.

This is a "dumb" version of vector search, for prototyping RAG responses and UIs — with both regular search (w/ Lunr) and vector search (with OpenAI embeddings + cosine similarity)

Usage:

import { semanticSearch } from "https://esm.town/v/yawnxyz/semanticSearch";

const documents = [
  { id: 1, content: 'cats dogs' },
  { id: 2, content: 'elephants giraffes lions tigers' },
  { id: 3, content: 'edam camembert cheddar' }
];

async function runExample() {
  // Add documents to the semantic search instance
  await semanticSearch.addDocuments(documents);

  const results = await semanticSearch.search('animals', 0, 3);
  console.log('Top 3 search results for "animals":');
  console.log(results);
}

runExample();

Migrated from folder: Libraries/SemanticSearch/semanticSearch