Fireworks LLM
Fireworks.ai focus on production use cases for open source LLMs, offering speed and quality.
import { Settings } from "llamaindex";import { FireworksLLM } from "@llamaindex/fireworks";
Settings.llm = new FireworksLLM({  apiKey: "<YOUR_API_KEY>",});Load and index documents
Section titled “Load and index documents”For this example, we will load the Berkshire Hathaway 2022 annual report pdf
const reader = new PDFReader();const documents = await reader.loadData("../data/brk-2022.pdf");
// Split text and create embeddings. Store them in a VectorStoreIndexconst index = await VectorStoreIndex.fromDocuments(documents);const queryEngine = index.asQueryEngine();const response = await queryEngine.query({  query: "What mistakes did Warren E. Buffett make?",});Full Example
Section titled “Full Example”import { VectorStoreIndex } from "llamaindex";import { PDFReader } from "llamaindex/readers/PDFReader";
async function main() {  // Load PDF  const reader = new PDFReader();  const documents = await reader.loadData("../data/brk-2022.pdf");
  // Split text and create embeddings. Store them in a VectorStoreIndex  const index = await VectorStoreIndex.fromDocuments(documents);
  // Query the index  const queryEngine = index.asQueryEngine();  const response = await queryEngine.query({    query: "What mistakes did Warren E. Buffett make?",  });
  // Output response  console.log(response.toString());}
main().catch(console.error);