Starter Tutorial
Make sure you have installed LlamaIndex.TS and have an OpenAI key. If you haven't, check out the installation guide.
From scratch(node.js + TypeScript):
In a new folder:
- npm
- Yarn
- pnpm
npm init
npm install -D typescript @types/node
yarn init
yarn add --dev typescript @types/node
pnpm init
pnpm add -D typescript @types/node
Create the file example.ts
. This code will load some example data, create a document, index it (which creates embeddings using OpenAI), and then creates query engine to answer questions about the data.
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);