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Azure OpenAI

To use Azure OpenAI, you only need to set a few environment variables together with the OpenAI class.

For example:

Environment Variables

export AZURE_OPENAI_KEY="<YOUR KEY HERE>"
export AZURE_OPENAI_ENDPOINT="<YOUR ENDPOINT, see https://learn.microsoft.com/en-us/azure/ai-services/openai/quickstart?tabs=command-line%2Cpython&pivots=rest-api>"
export AZURE_OPENAI_DEPLOYMENT="gpt-4" # or some other deployment name

Usage

import { OpenAI, serviceContextFromDefaults } from "llamaindex";

const azureOpenaiLLM = new OpenAI({ model: "gpt-4", temperature: 0 });

const serviceContext = serviceContextFromDefaults({ llm: azureOpenaiLLM });

Load and index documents

For this example, we will use a single document. In a real-world scenario, you would have multiple documents to index.

const document = new Document({ text: essay, id_: "essay" });

const index = await VectorStoreIndex.fromDocuments([document], {
serviceContext,
});

Query

const queryEngine = index.asQueryEngine();

const query = "What is the meaning of life?";

const results = await queryEngine.query({
query,
});

Full Example

import {
OpenAI,
Document,
VectorStoreIndex,
serviceContextFromDefaults,
} from "llamaindex";

async function main() {
// Create an instance of the LLM
const azureOpenaiLLM = new OpenAI({ model: "gpt-4", temperature: 0 });

// Create a service context
const serviceContext = serviceContextFromDefaults({ llm: azureOpenaiLLM });

const document = new Document({ text: essay, id_: "essay" });

// Load and index documents
const index = await VectorStoreIndex.fromDocuments([document], {
serviceContext,
});

// get retriever
const retriever = index.asRetriever();

// Create a query engine
const queryEngine = index.asQueryEngine({
retriever,
});

const query = "What is the meaning of life?";

// Query
const response = await queryEngine.query({
query,
});

// Log the response
console.log(response.response);
}