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);API Reference
Section titled “API Reference”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/