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*   Azure OpenAI

On this page

Azure OpenAI
============

[Azure OpenAI](https://azure.microsoft.com/products/ai-services/openai-service/) is a cloud service to help you quickly develop generative AI experiences with a diverse set of prebuilt and curated models from OpenAI, Meta and beyond.

LangChain.js supports integration with [Azure OpenAI](https://azure.microsoft.com/products/ai-services/openai-service/) using either the dedicated [Azure OpenAI SDK](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/openai/openai) or the [OpenAI SDK](https://github.com/openai/openai-node).

You can learn more about Azure OpenAI and its difference with the OpenAI API on [this page](https://learn.microsoft.com/azure/ai-services/openai/overview). If you don't have an Azure account, you can [create a free account](https://azure.microsoft.com/free/) to get started.

Using Azure OpenAI SDK[​](#using-azure-openai-sdk "Direct link to Using Azure OpenAI SDK")
------------------------------------------------------------------------------------------

You'll first need to install the [`@langchain/azure-openai`](https://www.npmjs.com/package/@langchain/azure-openai) package:

tip

See [this section for general instructions on installing integration packages](/v0.2/docs/how_to/installation#installing-integration-packages).

*   npm
*   Yarn
*   pnpm

    npm install -S @langchain/azure-openai

    yarn add @langchain/azure-openai

    pnpm add @langchain/azure-openai

tip

We're unifying model params across all packages. We now suggest using `model` instead of `modelName`, and `apiKey` for API keys.

You'll also need to have an Azure OpenAI instance deployed. You can deploy a version on Azure Portal following [this guide](https://learn.microsoft.com/azure/ai-services/openai/how-to/create-resource?pivots=web-portal).

Once you have your instance running, make sure you have the endpoint and key. You can find them in the Azure Portal, under the "Keys and Endpoint" section of your instance.

You can then define the following environment variables to use the service:

    AZURE_OPENAI_API_ENDPOINT=<YOUR_ENDPOINT>AZURE_OPENAI_API_KEY=<YOUR_KEY>AZURE_OPENAI_API_EMBEDDING_DEPLOYMENT_NAME=<YOUR_EMBEDDING_DEPLOYMENT_NAME>

Alternatively, you can pass the values directly to the `AzureOpenAI` constructor:

    import { AzureOpenAI } from "@langchain/azure-openai";const model = new AzureOpenAI({  azureOpenAIEndpoint: "<your_endpoint>",  apiKey: "<your_key>",  azureOpenAIApiDeploymentName: "<your_embedding_deployment_name",});

If you're using Azure Managed Identity, you can also pass the credentials directly to the constructor:

    import { DefaultAzureCredential } from "@azure/identity";import { AzureOpenAI } from "@langchain/azure-openai";const credentials = new DefaultAzureCredential();const model = new AzureOpenAI({  credentials,  azureOpenAIEndpoint: "<your_endpoint>",  azureOpenAIApiDeploymentName: "<your_embedding_deployment_name",});

### Usage example[​](#usage-example "Direct link to Usage example")

    import { AzureOpenAIEmbeddings } from "@langchain/azure-openai";const model = new AzureOpenAIEmbeddings();const res = await model.embedQuery(  "What would be a good company name for a company that makes colorful socks?");console.log({ res });

#### API Reference:

*   [AzureOpenAIEmbeddings](https://v02.api.js.langchain.com/classes/langchain_azure_openai.AzureOpenAIEmbeddings.html) from `@langchain/azure-openai`

Using OpenAI SDK[​](#using-openai-sdk "Direct link to Using OpenAI SDK")
------------------------------------------------------------------------

The `OpenAIEmbeddings` class can also use the OpenAI API on Azure to generate embeddings for a given text. By default it strips new line characters from the text, as recommended by OpenAI, but you can disable this by passing `stripNewLines: false` to the constructor.

For example, if your Azure instance is hosted under `https://{MY_INSTANCE_NAME}.openai.azure.com/openai/deployments/{DEPLOYMENT_NAME}`, you could initialize your instance like this:

tip

See [this section for general instructions on installing integration packages](/v0.2/docs/how_to/installation#installing-integration-packages).

*   npm
*   Yarn
*   pnpm

    npm install @langchain/openai

    yarn add @langchain/openai

    pnpm add @langchain/openai

    import { OpenAIEmbeddings } from "@langchain/openai";const embeddings = new OpenAIEmbeddings({  azureOpenAIApiKey: "YOUR-API-KEY", // In Node.js defaults to process.env.AZURE_OPENAI_API_KEY  azureOpenAIApiVersion: "YOUR-API-VERSION", // In Node.js defaults to process.env.AZURE_OPENAI_API_VERSION  azureOpenAIApiInstanceName: "{MY_INSTANCE_NAME}", // In Node.js defaults to process.env.AZURE_OPENAI_API_INSTANCE_NAME  azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}", // In Node.js defaults to process.env.AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME});

If you'd like to initialize using environment variable defaults, the `process.env.AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME` will be used first, then `process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME`. This can be useful if you're using these embeddings with another Azure OpenAI model.

If your instance is hosted under a domain other than the default `openai.azure.com`, you'll need to use the alternate `AZURE_OPENAI_BASE_PATH` environment variable. For example, here's how you would connect to the domain `https://westeurope.api.microsoft.com/openai/deployments/{DEPLOYMENT_NAME}`:

    import { OpenAIEmbeddings } from "@langchain/openai";const embeddings = new OpenAIEmbeddings({  azureOpenAIApiKey: "YOUR-API-KEY",  azureOpenAIApiVersion: "YOUR-API-VERSION",  azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}",  azureOpenAIBasePath:    "https://westeurope.api.microsoft.com/openai/deployments", // In Node.js defaults to process.env.AZURE_OPENAI_BASE_PATH});

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*   [Using Azure OpenAI SDK](#using-azure-openai-sdk)
    *   [Usage example](#usage-example)
*   [Using OpenAI SDK](#using-openai-sdk)

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