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Vector Index

import fs from "node:fs/promises";

import {
Document,
MetadataMode,
NodeWithScore,
VectorStoreIndex,
} from "llamaindex";

async function main() {
// Load essay from abramov.txt in Node
const path = "node_modules/llamaindex/examples/abramov.txt";

const essay = await fs.readFile(path, "utf-8");

// Create Document object with essay
const document = new Document({ text: essay, id_: path });

// Split text and create embeddings. Store them in a VectorStoreIndex
const index = await VectorStoreIndex.fromDocuments([document]);

// Query the index
const queryEngine = index.asQueryEngine();
const { response, sourceNodes } = await queryEngine.query({
query: "What did the author do in college?",
});

// Output response with sources
console.log(response);

if (sourceNodes) {
sourceNodes.forEach((source: NodeWithScore, index: number) => {
console.log(
`\n${index}: Score: ${source.score} - ${source.node.getContent(MetadataMode.NONE).substring(0, 50)}...\n`,
);
});
}
}

main().catch(console.error);