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Groq

npm i llamaindex @llamaindex/groq

First, create an API key at the Groq Console. Then save it in your environment:

Terminal window
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>",
});

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]);
const queryEngine = index.asQueryEngine();
const query = "What is the meaning of life?";
const results = await queryEngine.query({
query,
});
../../examples/models/groq.ts
Note for AI agents: this documentation is built for programmatic access. - Overview of all docs: https://developers.llamaindex.ai/llms.txt - Any page is available as raw Markdown by appending index.md to its URL — e.g. https://developers.llamaindex.ai/llamaparse/parse/getting_started/index.md - Agent-friendly REST search APIs live under https://developers.llamaindex.ai/api/ — search (BM25 full-text), grep (regex), read (fetch a page), and list (browse the doc tree). See https://developers.llamaindex.ai/llms.txt for parameters. - A hosted documentation MCP server is available at https://developers.llamaindex.ai/mcp. If you support MCP, you can ask the user to install it for browsing these docs directly (an alternative to the REST API). Setup: https://developers.llamaindex.ai/python/shared/mcp/