// Stream CRUD → events → embeddings in minutes
import { createConnection } from "@vectrail/sdk";

const conn = await createConnection({
  type: "postgres",
  url: process.env.DATABASE_URL,
});

await conn.enableVectorization({
  tables: ["users", "orders", "tickets"],
  embeddingModel: "text-embedding-3-large",
  chunking: { strategy: "auto", maxTokens: 400 },
});

const results = await conn.semanticSearch("refund policy for orders last week", {
  topK: 5,
  filter: { status: "resolved" },
});
console.log(results);