Released! FalkorDB 4.0-a1 – Vector Search Index & Bolt Protocol

            package com.falkordb;

import redis.clients.jedis.UnifiedJedis;
import redis.clients.jedis.graph.ResultSet;
import redis.clients.jedis.graph.Record;

public class FalkorDBVectorDemo {
  public static void main(String args[]) {
    try (UnifiedJedis jedis = new UnifiedJedis("redis://localhost:6379")) {

      // Create Vector index on field description in Character
      jedis.graphQuery("Books", "CREATE VECTOR INDEX FOR (c:Character) ON (c.description) OPTIONS {dimension:5, similarityFunction:'euclidean'}");

      // Fill in the Graph with some data on books and characters
      jedis.graphQuery("Books", "CREATE "
        + "(:Character {name:'Bastian Balthazar Bux', description:vecf32([0.1, 0.3, 0.3, 0.4, 0.7])})-[:in]->(book1:Book {name:'The Neverending Story'}), "
        + "(:Character {name:'Atreyu', description:vecf32([0.3, 0.6, 0.2, 0.1, 0.4])})-[:in]->(book1), "
        + "(:Character {name:'Jareth', description:vecf32([0.1, 0.3, 0.1, 0.2, 0.9])})-[:in]->(book2:Book {name:'Labyrinth'}), "
        + "(:Character {name:'Hoggle', description:vecf32([0.3, 0.2, 0.5, 0.7, 0.9])})-[:in]->(book2)");			

      // Find the book with the character description that is most similar (k=1) to the user's query
      ResultSet result = jedis.graphQuery("Books", "CALL db.idx.vector.queryNodes("
        + "'Character', 'description', 1, vecf32([0.1, 0.4, 0.3, 0.2, 0.7])) "
        + "YIELD entity "
        + "MATCH (entity)-[]->(b:Book) "
        + "RETURN b.name AS name");

      // Print out the name
      for (Record record : result) {
        System.out.println(record.getString("name"));
      }
    }
  }
}