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Azure OpenAI

To use Azure OpenAI, you only need to install the @llamaindex/azure package:

npm i llamaindex @llamaindex/azure

The class AzureOpenAI is used for setting the LLM and AzureOpenAIEmbedding is used for setting the embedding model, e.g.:

import { Settings } from "llamaindex";
import { AzureOpenAI, AzureOpenAIEmbedding } from "@llamaindex/azure";
Settings.llm = new AzureOpenAI({
apiKey: '[key]',
deployment: '[model]',
apiVersion: '[version]',
endpoint: `https://[deployment].openai.azure.com/`,
});
Settings.embedModel = new AzureOpenAIEmbedding({
apiKey: '[key]',
deployment: '[embedding-model]',
apiVersion: '[version]',
endpoint: `https://[deployment].openai.azure.com/`,
});

Instead of explicitly setting the API key, deployment, version, and endpoint in the constructor, you can use the following environment variables: AZURE_OPENAI_DEPLOYMENT for the model deployment name, AZURE_OPENAI_KEY for your API key, AZURE_OPENAI_ENDPOINT for your Azure endpoint URL, and AZURE_OPENAI_API_VERSION for the API version.

See the Azure examples for more examples of how to use Azure OpenAI.

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/