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Document Stores

Document stores contain ingested document chunks, i.e. Nodes.

Check the LlamaIndexTS Github for the most up to date overview of integrations.

npm i llamaindex @llamaindex/postgres

You can configure the schemaName, tableName, namespace, and connectionString. If a connectionString is not provided, it will use the environment variables PGHOST, PGUSER, PGPASSWORD, PGDATABASE and PGPORT.

import { Document, VectorStoreIndex, storageContextFromDefaults } from "llamaindex";
import { PostgresDocumentStore } from "@llamaindex/postgres";
const storageContext = await storageContextFromDefaults({
docStore: new PostgresDocumentStore(),
});
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/