Groq
Installation
npm i llamaindex @llamaindex/groq
pnpm add llamaindex @llamaindex/groq
yarn add llamaindex @llamaindex/groq
bun add llamaindex @llamaindex/groq
Usage
First, create an API key at the Groq Console. Then save it in your environment:
export GROQ_API_KEY=<your-api-key>
The initialize the Groq module.
import { Groq } from "@llamaindex/groq";
import { Settings } from "llamaindex";
Settings.llm = new Groq({
// If you do not wish to set your API key in the environment, you may
// configure your API key when you initialize the Groq class.
// apiKey: "<your-api-key>",
});
Load and index documents
For this example, we will use a single document. In a real-world scenario, you would have multiple documents to index.
import { Document, VectorStoreIndex } from "llamaindex";
const document = new Document({ text: essay, id_: "essay" });
const index = await VectorStoreIndex.fromDocuments([document]);
Query
const queryEngine = index.asQueryEngine();
const query = "What is the meaning of life?";
const results = await queryEngine.query({
query,
});
Full Example
import fs from "node:fs/promises";
import { Groq } from "@llamaindex/groq";
import { HuggingFaceEmbedding } from "@llamaindex/huggingface";
import { Document, Settings, VectorStoreIndex } from "llamaindex";
// Update llm to use Groq
Settings.llm = new Groq({
apiKey: process.env.GROQ_API_KEY,
});
// Use HuggingFace for embeddings
Settings.embedModel = new HuggingFaceEmbedding({
modelType: "Xenova/all-mpnet-base-v2",
});
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");
const document = new Document({ text: essay, id_: "essay" });
// Load and index documents
const index = await VectorStoreIndex.fromDocuments([document]);
// get retriever
const retriever = index.asRetriever();
// Create a query engine
const queryEngine = index.asQueryEngine({
retriever,
});
const query = "What is the meaning of life?";
// Query
const { message } = await queryEngine.query({
query,
});
// Log the response
console.log(message.content);
}
main().catch(console.error);
API Reference
Edit on GitHub
Last updated on