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Storage

Storage in LlamaIndex.TS works automatically once you’ve configured a StorageContext object.

Per default a local directory is used for storage. Depening on the storage type (i.e. doc stores, index stores or vector stores), you can configure a different persistence layer. Most commonly a vector database is used as vector store.

You can configure the persistDir to define where to store the data locally.

import {
Document,
VectorStoreIndex,
storageContextFromDefaults,
} from "llamaindex";
const storageContext = await storageContextFromDefaults({
persistDir: "./storage",
});
const document = new Document({ text: "Test Text" });
const index = await VectorStoreIndex.fromDocuments([document], {
storageContext,
});
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/