@@ -4,7 +4,7 @@ titleSuffix: Azure OpenAI
 description: Learn about the model deprecations and retirements in Azure OpenAI.
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 09/09/2024
+ms.date: 09/12/2024
 ms.custom: 
 manager: nitinme
 author: mrbullwinkle
@@ -91,9 +91,9 @@ These models are currently available for use in Azure OpenAI Service.
 
 | Model | Version | Retirement date | Suggested replacements |
 | ---- | ---- | ---- | --- |
-| `gpt-35-turbo` | 0301 | January 27, 2025<br><br> Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 15, 2024.   | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini`  |
-| `gpt-35-turbo`<br>`gpt-35-turbo-16k` | 0613 | January 27, 2025 <br><br> Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 15, 2024.  | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini`|
-| `gpt-35-turbo` | 1106 | No earlier than Nov 17, 2024 <br><br> Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 15, 2024. | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini` |
+| `gpt-35-turbo` | 0301 | January 27, 2025<br><br> Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 13, 2024.   | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini`  |
+| `gpt-35-turbo`<br>`gpt-35-turbo-16k` | 0613 | January 27, 2025 <br><br> Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 13, 2024.  | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini`|
+| `gpt-35-turbo` | 1106 | No earlier than Nov 17, 2024 <br><br> Deployments set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 13, 2024. | `gpt-35-turbo` (0125) <br><br> `gpt-4o-mini` |
 | `gpt-35-turbo` | 0125 | No earlier than Feb 22, 2025 | `gpt-4o-mini` |
 | `gpt-4`<br>`gpt-4-32k` | 0314 | June 6, 2025 | `gpt-4o` |
 | `gpt-4`<br>`gpt-4-32k` | 0613 | June 6, 2025 | `gpt-4o` |
@@ -115,7 +115,7 @@ These models are currently available for use in Azure OpenAI Service.
 
 | Model | Current default version | New default version | Default upgrade date |
 |---|---|---|---|
-| `gpt-35-turbo` | 0301 | 0125 | Deployments of versions `0301`, `0613`, and `1106` set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 15, 2024.|
+| `gpt-35-turbo` | 0301 | 0125 | Deployments of versions `0301`, `0613`, and `1106` set to [**Auto-update to default**](/azure/ai-services/openai/how-to/working-with-models?tabs=powershell#auto-update-to-default) will be automatically upgraded to version: `0125`, starting on November 13, 2024.|
 
 
 
@@ -158,6 +158,10 @@ If you're an existing customer looking for information about these models, see [
 
 ## Retirement and deprecation history
 
+## September 12, 2024
+
+* `gpt-35-turbo` (0301), (0613), (1106) and `gpt-35-turbo-16k` (0613) auto-update to default upgrade date updated to November 13, 2024.
+
 ## September 9, 2024
 
 * `gpt-35-turbo` (0301) and (0613) retirement changed to January 27, 2025.

@@ -5,11 +5,11 @@ description: Learn how to get started generating images with Azure OpenAI Servic
 #services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
-ms.custom: devx-track-python, devx-track-dotnet, devx-track-extended-java, devx-track-go, devx-track-js
+ms.custom: devx-track-python, devx-track-dotnet, devx-track-extended-java, devx-track-go, devx-track-js, devx-track-ts
 ms.topic: quickstart
 author: PatrickFarley
 ms.author: pafarley
-ms.date: 08/21/2024
+ms.date: 09/06/2024
 zone_pivot_groups: openai-quickstart-dall-e
 ---
 

@@ -5,7 +5,7 @@ description: Use this article to get started using Azure OpenAI to deploy and us
 services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
-ms.custom: devx-track-python
+ms.custom: devx-track-python, devx-track-js, devx-track-ts
 ms.topic: quickstart
 author: PatrickFarley
 ms.author: pafarley
@@ -39,6 +39,12 @@ Get started using GPT-4 Turbo with images with the Azure OpenAI Service.
 
 ::: zone-end
 
+::: zone pivot="programming-language-javascript"
+
+[!INCLUDE [JavaScript quickstart](includes/gpt-v-javascript.md)]
+
+::: zone-end
+
 ## Next steps
 
 * Learn more about these APIs in the [GPT-4 Turbo with Vision how-to guide](./gpt-v-quickstart.md)

@@ -20,6 +20,9 @@ JSON mode allows you to set the models response format to return a valid JSON ob
 > [!NOTE]
 > While JSON mode is still supported, when possible we recommend using [structured outputs](./structured-outputs.md). Like JSON mode structured outputs generates valid JSON, but with the added benefit that you can constrain the model to use a specific JSON schema.
 
+>[!NOTE]
+> Currently Structured outputs is not supported on [bring your own data](../concepts/use-your-data.md) scenario.
+
 ## JSON mode support
 
 JSON mode is only currently supported with the following models:

@@ -75,7 +75,17 @@ After you purchase a commitment on your quota, you can create a deployment. To c
 
 Important things to note: 
 * The deployment dialog contains a reminder that you can purchase an Azure Reservation for Azure OpenAI Provisioned to obtain a significant discount for a term commitment. 
-* There is a message that tells you the list, hourly price of the deployment that you would be charged if this deployment is not covered by a reservation.  This is a list price that does not include any negotiated discounts for your company. 
+
+Once you have entered the deployment settings, click **Confirm Pricing** to continue.  A pricing confirmation dialog will appear that will display the list price for the deployment, if you choose to pay for it on an hourly basis, with no Azure Reservation to provide a term discount.
+
+If you are unsure of the costs, cancel the deployment and proceed once you understand the payment model and underlying costs for provisioned deployment. This step may prevent unexpected, high charges on your payment invoice. Resources to educate yourself include: 
+
+* [Azure Pricing Portal](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) 
+* [Understanding the provisioned throughput purchase model](provisioned-throughput-onboarding.md#understanding-the-provisioned-throughput-purchase-model) 
+
+The image below shows the pricing confirmation you will see. The price shown is an example only. 
+
+:::image type="content" source="../media/provisioned/confirm-pricing.png" alt-text="Screenshot showing the pricing confirmation screen." lightbox="../media/provisioned/confirm-pricing.png":::
 
 If you wish to create your deployment programmatically, you can do so with the following Azure CLI command. Update the `sku-capacity` with the desired number of provisioned throughput units.
 
@@ -110,16 +120,17 @@ Things to notice:
 
 Selecting a resource and clicking **Switch resource** will cause the deployment dialog to redisplay using the selected resource. You can then proceed to create your deployment in the new region. 
 
-Learn more about the purchase model and how to purchase a reservation: 
-
-* [Azure OpenAI provisioned onboarding guide](./provisioned-throughput-onboarding.md) 
-* [Guide for Azure OpenAI provisioned reservations](../concepts/provisioned-throughput.md) 
-
 ## Optionally purchase a reservation 
 
 Following the creation of your deployment, you might want to purchase a term discount via an Azure Reservation.  An Azure Reservation can provide a substantial discount on the hourly rate for users intending to use the deployment beyond a few days.   
 
-For more information on purchasing a reservation, see [Save costs with Microsoft Azure OpenAI service Provisioned Reservations](/azure/cost-management-billing/reservations/azure-openai).
+For more information on the purchase model and reservations, see:
+* [Save costs with Microsoft Azure OpenAI service provisioned reservations](/azure/cost-management-billing/reservations/azure-openai).
+* [Azure OpenAI provisioned onboarding guide](./provisioned-throughput-onboarding.md) 
+* [Guide for Azure OpenAI provisioned reservations](../concepts/provisioned-throughput.md) 
+
+> [!IMPORTANT]
+> Capacity availability for model deployments is dynamic and changes frequently across regions and models. To prevent you from purchasing a reservation for more PTUs than you can use, create deployments first, and then purchase the Azure Reservation to cover the PTUs you have deployed. This best practice will ensure that you can take full advantage of the reservation discount and prevent you from purchasing a term commitment that you cannot use.
 
 ## Make your first inferencing calls
 The inferencing code for provisioned deployments is the same a standard deployment type. The following code snippet shows a chat completions call to a GPT-4 model. For your first time using these models programmatically, we recommend starting with our [quickstart guide](../quickstart.md). Our recommendation is to use the OpenAI library with version 1.0 or greater since this includes retry logic within the library.

@@ -3,7 +3,7 @@ title: Azure OpenAI Service Provisioned Throughput Units (PTU) onboarding
 description: Learn about provisioned throughput units onboarding and Azure OpenAI. 
 ms.service: azure-ai-openai
 ms.topic: conceptual 
-ms.date: 08/07/2024
+ms.date: 09/12/2024
 manager: nitinme
 author: mrbullwinkle 
 ms.author: mbullwin 
@@ -81,6 +81,7 @@ Customers that require long-term usage of provisioned deployments, however, migh
 > It is not recommended to scale production deployments according to incoming traffic and pay for them purely on an hourly basis. There are two reasons for this:
 > * The cost savings achieved by purchasing an Azure Reservation for Azure OpenAI Provisioned are significant, and it will be less expensive in many cases to maintain a deployment sized for full production volume paid for via a reservation than it would be to scale the deployment with incoming traffic.
 > * Having unused provisioned quota (PTUs) does not guarentee that capacity will be available to support increasing the size of the deployment when required. Quota limits the maximum number of PTUs that can be deployed, but it is not a capacity guarantee. Provisioned capacity for each region and modal dynamically changes throughout the day and might not be available when required. As a result, it is recommended to maintain a permanant deployment to cover your traffic needs (paid for via a reservation).
+> * Charges for deployments on a deleted resource will continue until the resource is purged.  To prevent this, delete a resource’s deployment before deleting the resource.  For more information, see [Recover or purge deleted Azure AI services resources](../../recover-purge-resources.md). 
 
 ## Azure Reservations for Azure OpenAI Provisioned   
 
@@ -103,9 +104,11 @@ Discounts on top of the hourly usage price can be obtained by purchasing an Azur
 * If the size of provisioned deployments within the scope of a reservation exceeds the amount of the reservation, the excess is charged at the hourly rate. For example, if deployments amounting to 250 PTUs exist within the scope of a 200 PTU reservation, 50 PTUs will be charged on an hourly basis until the deployment sizes are reduced to 200 PTUs, or a new reservation is created to cover the remaining 50. 
 
 * Reservations guarantee a discounted price for the selected term.  They do not reserve capacity on the service or guarantee that it will be available when a deployment is created.  It is highly recommended that customers create deployments prior to purchasing a reservation to prevent from over-purchasing a reservation. 
- 
-> [!NOTE]
-> The Azure role and tenant policy requirements to purchase a reservation are different than those required to create a deployment or Azure OpenAI resource. See Azure OpenAI [Provisioned reservation documentation](https://aka.ms/oai/docs/ptum-reservations) for more details.
+
+> [!IMPORTANT] 
+> * Capacity availability for model deployments is dynamic and changes frequently across regions and models.  To prevent you from purchasing a reservation for more PTUs than you can use, create deployments first, and then purchase the Azure Reservation to cover the PTUs you have deployed.  This best practice will ensure that you can take full advantage of the reservation discount and prevent you from purchasing a term commitment that you cannot use. 
+>
+> * The Azure role and tenant policy requirements to purchase a reservation are different than those required to create a deployment or Azure OpenAI resource.  Verify authorization to purchase reservations in advance of needing to do so. See Azure OpenAI [Provisioned reservation documentation](https://aka.ms/oai/docs/ptum-reservations) for more details.
 
 ## Important: Sizing Azure OpenAI Provisioned Reservations 
 
@@ -119,7 +122,7 @@ To assist customers with purchasing the correct reservation amounts. The total n
 
 Managing Azure Reservations 
 
-After a reservation is created, it is a best practice monitor it to ensure it is receiving the usage you are expecting.  This may be done via the Azure Reservation Portal or Azure Monitor.  Details on these topics and others can be found here: 
+After a reservation is created, it is a best practice monitor it to ensure it is receiving the usage you are expecting.  This can be done via the Azure Reservation Portal or Azure Monitor.  Details on these topics and others can be found here: 
 
 * [View Azure reservation utilization](/azure/cost-management-billing/reservations/reservation-utilization) 
 * [View Azure Reservation purchase and refund transactions](/azure/cost-management-billing/reservations/view-purchase-refunds) 

@@ -16,6 +16,9 @@ recommendations: false
 
 Structured outputs make a model follow a [JSON Schema](https://json-schema.org/overview/what-is-jsonschema) definition that you provide as part of your inference API call. This is in contrast to the older [JSON mode](./json-mode.md) feature, which guaranteed valid JSON would be generated, but was unable to ensure strict adherence to the supplied schema. Structured outputs is recommended for function calling, extracting structured data, and building complex multi-step workflows.
 
+>[!NOTE]
+> Currently Structured outputs is not supported on [bring your own data](../concepts/use-your-data.md) scenario.
+
 ## Supported models
 
 Currently only `gpt-4o` version: `2024-08-06` supports structured outputs.

@@ -8,19 +8,30 @@ ms.service: azure-ai-openai
 ms.topic: include
 author: PatrickFarley
 ms.author: pafarley
-ms.date: 08/24/2023
+ms.date: 09/06/2024
 ---
 
 Use this guide to get started generating images with the Azure OpenAI SDK for JavaScript.
 
-[Library source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/openai/openai) | [Package (npm)](https://www.npmjs.com/package/@azure/openai) | [Samples](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/openai/Azure.AI.OpenAI/tests/Samples)
+[Reference documentation](https://platform.openai.com/docs/api-reference/images/create) | [Source code](https://github.com/openai/openai-node) | [Package (npm)](https://www.npmjs.com/package/openai) | [Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/openai/openai/samples)
 
 ## Prerequisites
 
+#### [TypeScript](#tab/typescript)
+
+- An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services?azure-portal=true)
+- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)
+- [TypeScript](https://www.typescriptlang.org/download/)
+- An Azure OpenAI resource created in a supported region (see [Region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability)). For more information, see [Create a resource and deploy a model with Azure OpenAI](../how-to/create-resource.md).
+
+
+#### [JavaScript](#tab/javascript)
+
 - An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services?azure-portal=true)
 - [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)
 - An Azure OpenAI resource created in a supported region (see [Region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability)). For more information, see [Create a resource and deploy a model with Azure OpenAI](../how-to/create-resource.md).
 
+---
 
 ## Setup
 
@@ -39,10 +50,10 @@ npm init
 
 ## Install the client library
 
-Install the Azure OpenAI client library for JavaScript with npm:
+Install the client libraries with:
 
 ```console
-npm install @azure/openai
+npm install openai @azure/identity
 ```
 
 Your app's _package.json_ file will be updated with the dependencies.
@@ -51,43 +62,123 @@ Your app's _package.json_ file will be updated with the dependencies.
 
 Create a new file named _ImageGeneration.js_ and open it in your preferred code editor. Copy the following code into the _ImageGeneration.js_ file:
 
-```javascript
-const { OpenAIClient, AzureKeyCredential } = require("@azure/openai");
+#### [TypeScript](#tab/typescript)
+
+```typescript
+import "dotenv/config";
+import { AzureOpenAI } from "openai";
 
 // You will need to set these environment variables or edit the following values
-const endpoint = process.env["AZURE_OPENAI_ENDPOINT"] ;
-const azureApiKey = process.env["AZURE_OPENAI_API_KEY"] ;
+const endpoint = process.env["AZURE_OPENAI_ENDPOINT"];
+const apiKey = process.env["AZURE_OPENAI_API_KEY"];
+
+// Required Azure OpenAI deployment name and API version
+const apiVersion = "2024-07-01";
+const deploymentName = "dall-e-3";
 
 // The prompt to generate images from
 const prompt = "a monkey eating a banana";
-const size = "256x256";
+const numberOfImagesToGenerate = 1;
+
+function getClient(): AzureOpenAI {
+  return new AzureOpenAI({
+    endpoint,
+    apiKey,
+    apiVersion,
+    deployment: deploymentName,
+  });
+}
+async function main() {
+  console.log("== Image Generation ==");
+
+  const client = getClient();
+
+  const results = await client.images.generate({
+    prompt,
+    size: "1024x1024",
+    n: numberOfImagesToGenerate,
+    model: "",
+    style: "vivid", // or "natural"
+  });
+
+  for (const image of results.data) {
+    console.log(`Image generation result URL: ${image.url}`);
+  }
+}
+
+main().catch((err) => {
+  console.error("The sample encountered an error:", err);
+});
+```
+
+1. Build the application with the following command:
+
+    ```console
+    tsc
+    ```
+
+1. Run the application with the following command:
 
-// The number of images to generate
-const n = 2;
+    ```console
+    node ImageGeneration.js
+    ```
 
+
+#### [JavaScript](#tab/javascript)
+
+```javascript
+require("dotenv/config");
+const { AzureOpenAI } = require("openai");
+
+// You will need to set these environment variables or edit the following values
+const endpoint = process.env["AZURE_OPENAI_ENDPOINT"];
+const apiKey = process.env["AZURE_OPENAI_API_KEY"];
+
+// Required Azure OpenAI deployment name and API version
+const apiVersion = "2024-07-01";
+const deploymentName = "dall-e-3";
+
+// The prompt to generate images from
+const prompt = "a monkey eating a banana";
+const numberOfImagesToGenerate = 1;
+
+function getClient() {
+  return new AzureOpenAI({
+    endpoint,
+    apiKey,
+    apiVersion,
+    deployment: deploymentName,
+  });
+}
 async function main() {
-    console.log("== Batch Image Generation ==");
-  
-    const client = new OpenAIClient(endpoint, new AzureKeyCredential(azureApiKey));
-    const deploymentName = "dall-e";
-    const results = await client.getImages(deploymentName, prompt, { n, size });
-  
-    for (const image of results.data) {
-      console.log(`Image generation result URL: ${image.url}`);
-    }
-    //console.log(`Image generation result URL: ${results.result.status}`);
+  console.log("== Image Generation ==");
+
+  const client = getClient();
+
+  const results = await client.images.generate({
+    prompt,
+    size: "1024x1024",
+    n: numberOfImagesToGenerate,
+    model: "",
+    style: "vivid", // or "natural"
+  });
+
+  for (const image of results.data) {
+    console.log(`Image generation result URL: ${image.url}`);
+  }
 }
 
 main().catch((err) => {
-console.error("The sample encountered an error:", err);
+  console.error("The sample encountered an error:", err);
 });
 ```
 
 Run the script with the following command:
 
 ```console
-node _ImageGeneration.js
+node ImageGeneration.js
 ```
+---
 
 ## Output
 

@@ -0,0 +1,246 @@
+---
+title: 'Quickstart: Use GPT-4 Turbo with Vision on your images and videos with the JavaScript SDK'
+titleSuffix: Azure OpenAI
+description: Get started using the OpenAI JavaScript SDK to deploy and use the GPT-4 Turbo with Vision model.
+services: cognitive-services
+manager: nitinme
+ms.service: azure-ai-openai
+ms.topic: include
+ms.custom: references_regions
+ms.date: 09/06/2024
+---
+
+Use this article to get started using the OpenAI JavaScript SDK to deploy and use the GPT-4 Turbo with Vision model. 
+
+This SDK is provided by OpenAI with Azure specific types provided by Azure. 
+
+[Reference documentation](https://platform.openai.com/docs/api-reference/chat) | [Library source code](https://github.com/openai/openai-node?azure-portal=true) | [Package (npm)](https://www.npmjs.com/package/openai) | [Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/openai/openai/samples)
+
+## Prerequisites
+
+## [**TypeScript**](#tab/typescript)
+
+- An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services?azure-portal=true)
+- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)
+- [TypeScript](https://www.typescriptlang.org/download/)
+- An Azure OpenAI resource created in a supported region (see [Region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability)). For more information, see [Create a resource and deploy a model with Azure OpenAI](../how-to/create-resource.md).
+
+
+## [**JavaScript**](#tab/javascript)
+
+- An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services?azure-portal=true)
+- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)
+- An Azure OpenAI resource created in a supported region (see [Region availability](/azure/ai-services/openai/concepts/models#model-summary-table-and-region-availability)). For more information, see [Create a resource and deploy a model with Azure OpenAI](../how-to/create-resource.md).
+
+---
+
+
+> [!NOTE]
+> This library is maintained by OpenAI. Refer to the [release history](https://github.com/openai/openai-node/releases) to track the latest updates to the library.
+
+[!INCLUDE [get-key-endpoint](get-key-endpoint.md)]
+
+[!INCLUDE [environment-variables](environment-variables.md)]
+
+
+## Create a Node application
+
+In a console window (such as cmd, PowerShell, or Bash), create a new directory for your app, and navigate to it. Then run the `npm init` command to create a node application with a _package.json_ file.
+
+```console
+npm init
+```
+
+## Install the client library
+
+Install the client libraries with:
+
+```console
+npm install openai @azure/identity
+```
+
+Your app's _package.json_ file will be updated with the dependencies.
+
+## Create a new JavaScript application for image prompts
+
+Select an image from the [azure-samples/cognitive-services-sample-data-files](https://github.com/Azure-Samples/cognitive-services-sample-data-files/tree/master/ComputerVision/Images) and set the URL for an image in the environment variables.
+
+## [**TypeScript**](#tab/typescript)
+
+1. Create a _quickstart.ts_ and paste in the following code. 
+    
+    ```typescript
+    import "dotenv/config";
+    import { AzureOpenAI } from "openai";
+    import type {
+      ChatCompletion,
+      ChatCompletionCreateParamsNonStreaming,
+    } from "openai/resources/index";
+    
+    // You will need to set these environment variables or edit the following values
+    const endpoint = process.env["AZURE_OPENAI_ENDPOINT"] || "<endpoint>";
+    const apiKey = process.env["AZURE_OPENAI_API_KEY"] || "<api key>";
+    const imageUrl = process.env["IMAGE_URL"] || "<image url>";
+    
+    // Required Azure OpenAI deployment name and API version
+    const apiVersion = "2024-07-01-preview";
+    const deploymentName = "gpt-4-with-turbo";
+    
+    function getClient(): AzureOpenAI {
+      return new AzureOpenAI({
+        endpoint,
+        apiKey,
+        apiVersion,
+        deployment: deploymentName,
+      });
+    }
+    function createMessages(): ChatCompletionCreateParamsNonStreaming {
+      return {
+        messages: [
+          { role: "system", content: "You are a helpful assistant." },
+          {
+            role: "user",
+            content: [
+              {
+                type: "text",
+                text: "Describe this picture:",
+              },
+              {
+                type: "image_url",
+                image_url: {
+                  url: imageUrl,
+                },
+              },
+            ],
+          },
+        ],
+        model: "",
+        max_tokens: 2000,
+      };
+    }
+    async function printChoices(completion: ChatCompletion): Promise<void> {
+      for (const choice of completion.choices) {
+        console.log(choice.message);
+      }
+    }
+    export async function main() {
+      console.log("== Get GPT-4 Turbo with vision Sample ==");
+    
+      const client = getClient();
+      const messages = createMessages();
+      const completion = await client.chat.completions.create(messages);
+      await printChoices(completion);
+    }
+    
+    main().catch((err) => {
+      console.error("Error occurred:", err);
+    });
+    ```
+1. Make the following changes:
+    1. Enter the name of your GPT-4 Turbo with Vision deployment in the appropriate field.
+    1. Change the value of the `"url"` field to the URL of your image.
+        > [!TIP]
+        > You can also use a base 64 encoded image data instead of a URL. For more information, see the [GPT-4 Turbo with Vision how-to guide](../how-to/gpt-with-vision.md#use-a-local-image).
+
+1. Build the application with the following command:
+
+    ```console
+    tsc
+    ```
+
+1. Run the application with the following command:
+
+    ```console
+    node quickstart.js
+    ```
+
+
+## [**JavaScript**](#tab/javascript)
+
+1. Replace the contents of _quickstart.js_ with the following code. 
+    
+    ```javascript
+    import "dotenv/config";
+    import { AzureOpenAI } from "openai";
+    
+    // You will need to set these environment variables or edit the following values
+    const endpoint = process.env["AZURE_OPENAI_ENDPOINT"] || "<endpoint>";
+    const apiKey = process.env["AZURE_OPENAI_API_KEY"] || "<api key>";
+    const imageUrl = process.env["IMAGE_URL"] || "<image url>";
+    
+    // Required Azure OpenAI deployment name and API version
+    const apiVersion = "2024-07-01-preview";
+    const deploymentName = "gpt-4-with-turbo";
+    
+    function getClient() {
+      return new AzureOpenAI({
+        endpoint,
+        apiKey,
+        apiVersion,
+        deployment: deploymentName,
+      });
+    }
+    function createMessages() {
+      return {
+        messages: [
+          { role: "system", content: "You are a helpful assistant." },
+          {
+            role: "user",
+            content: [
+              {
+                type: "text",
+                text: "Describe this picture:",
+              },
+              {
+                type: "image_url",
+                image_url: {
+                  url: imageUrl,
+                },
+              },
+            ],
+          },
+        ],
+        model: "",
+        max_tokens: 2000,
+      };
+    }
+    async function printChoices(completion) {
+      for (const choice of completion.choices) {
+        console.log(choice.message);
+      }
+    }
+    export async function main() {
+      console.log("== Get GPT-4 Turbo with vision Sample ==");
+    
+      const client = getClient();
+      const messages = createMessages();
+      const completion = await client.chat.completions.create(messages);
+      await printChoices(completion);
+    }
+    
+    main().catch((err) => {
+      console.error("Error occurred:", err);
+    });
+    ```
+
+1. Make the following changes:
+    1. Enter the name of your GPT-4 Turbo with Vision deployment in the appropriate field.
+    1. Change the value of the `"url"` field to the URL of your image.
+        > [!TIP]
+        > You can also use a base 64 encoded image data instead of a URL. For more information, see the [GPT-4 Turbo with Vision how-to guide](../how-to/gpt-with-vision.md#use-a-local-image).
+1. Run the application with the following command:
+
+    ```console
+    node quickstart.js
+    ```
+
+---
+
+## Clean up resources
+
+If you want to clean up and remove an Azure OpenAI resource, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+
+- [Azure portal](../../multi-service-resource.md?pivots=azportal#clean-up-resources)
+- [Azure CLI](../../multi-service-resource.md?pivots=azcli#clean-up-resources)
+
+

@@ -5,7 +5,7 @@ author: glharper
 ms.author: glharper
 ms.service: azure-ai-openai
 ms.topic: include
-ms.date: 03/04/2024
+ms.date: 09/06/2024
 ---
 
 [!INCLUDE [Set up required variables](./use-your-data-common-variables.md)]
@@ -23,81 +23,214 @@ npm init
 
 Install the Azure OpenAI client and Azure Identity libraries for JavaScript with npm:
 
+#### [TypeScript](#tab/typescript)
+
+```console
+npm install openai @azure/identity @azure/openai 
+```
+
+The `@azure/openai/types` dependency is included to extend the Azure OpenAI model for the `data_sources` property. This import is only necessary for TypeScript.
+
+#### [JavaScript](#tab/javascript)
+
 ```console
 npm install @azure/openai @azure/identity
 ```
 
+---
+
 Your app's _package.json_ file will be updated with the dependencies.
 
 ## Create a sample application
 
-Open a command prompt where you want the new project, and create a new file named ChatWithOwnData.js. Copy the following code into the ChatWithOwnData.js file.
-
-
-
-```javascript
-const { OpenAIClient, AzureKeyCredential } = require("@azure/openai");
-
-// Set the Azure and AI Search values from environment variables
-const endpoint = process.env["AZURE_OPENAI_ENDPOINT"];
-const azureApiKey = process.env["AZURE_OPENAI_API_KEY"];
-const deploymentId = process.env["AZURE_OPENAI_DEPLOYMENT_ID"];
-const searchEndpoint = process.env["AZURE_AI_SEARCH_ENDPOINT"];
-const searchKey = process.env["AZURE_AI_SEARCH_API_KEY"];
-const searchIndex = process.env["AZURE_AI_SEARCH_INDEX"];
-
-
-async function main(){
-  const client = new OpenAIClient(endpoint, new AzureKeyCredential(azureApiKey));
-
-  const messages = [
-    { role: "user", content: "What are my available health plans?" },
-  ];
-
-  console.log(`Message: ${messages.map((m) => m.content).join("\n")}`);
-
-  const events = await client.streamChatCompletions(deploymentId, messages, { 
-    maxTokens: 128,
-    azureExtensionOptions: {
-      extensions: [
-        {
-          type: "AzureCognitiveSearch",
-          endpoint: searchEndpoint,
-          key: searchKey,
-          indexName: searchIndex,
-        },
-      ],
-    },
-  });
-  let response = "";
-  for await (const event of events) {
-    for (const choice of event.choices) {
-      const newText = choice.delta?.content;
-      if (!!newText) {
-        response += newText;
-        // To see streaming results as they arrive, uncomment line below
-        // console.log(newText);
+#### [TypeScript](#tab/typescript)
+
+1. Open a command prompt where you want the new project, and create a new file named `ChatWithOwnData.ts`. Copy the following code into the `ChatWithOwnData.ts` file.
+    
+    ```typescript
+    import "dotenv/config";
+    import { AzureOpenAI } from "openai";
+    import "@azure/openai/types";
+    
+    // Set the Azure and AI Search values from environment variables
+    const endpoint = process.env["AZURE_OPENAI_ENDPOINT"];
+    const apiKey = process.env["AZURE_OPENAI_API_KEY"];
+    const searchEndpoint = process.env["AZURE_AI_SEARCH_ENDPOINT"];
+    const searchKey = process.env["AZURE_AI_SEARCH_API_KEY"];
+    const searchIndex = process.env["AZURE_AI_SEARCH_INDEX"];
+    
+    // Required Azure OpenAI deployment name and API version
+    const deploymentName = "gpt-4";
+    const apiVersion = "2024-07-01-preview";
+    
+    function getClient(): AzureOpenAI {
+      return new AzureOpenAI({
+        endpoint,
+        apiKey,
+        deployment: deploymentName,
+        apiVersion,
+      });
+    }
+    
+    async function main() {
+      const client = getClient();
+    
+      const messages = [
+        { role: "user", content: "What are my available health plans?" },
+      ];
+    
+      console.log(`Message: ${messages.map((m) => m.content).join("\n")}`);
+    
+      const events = await client.chat.completions.create({
+        stream: true,
+        messages: [
+          {
+            role: "user",
+            content:
+              "What's the most common feedback we received from our customers about the product?",
+          },
+        ],
+        max_tokens: 128,
+        model: "",
+        data_sources: [
+          {
+            type: "azure_search",
+            parameters: {
+              endpoint: searchEndpoint,
+              index_name: searchIndex,
+              authentication: {
+                type: "api_key",
+                key: searchKey,
+              },
+            },
+          },
+        ],
+      });
+    
+      let response = "";
+      for await (const event of events) {
+        for (const choice of event.choices) {
+          const newText = choice.delta?.content;
+          if (newText) {
+            response += newText;
+            // To see streaming results as they arrive, uncomment line below
+            // console.log(newText);
+          }
+        }
       }
+      console.log(response);
     }
-  }
-  console.log(response);
-}
-
-main().catch((err) => {
-  console.error("The sample encountered an error:", err);
-});
+    
+    main().catch((err) => {
+      console.error("The sample encountered an error:", err);
+    });
+    ```
+
+1. Build the application with the following command:
+
+    ```console
+    tsc
+    ```
+
+1. Run the application with the following command:
+
+    ```console
+    node ChatWithOwnData.js
+    ```
+
+#### [JavaScript](#tab/javascript)
+
+1. Open a command prompt where you want the new project, and create a new file named `ChatWithOwnData.js`. Copy the following code into the `ChatWithOwnData.js` file.
+    
+    ```javascript
+    require("dotenv/config");
+    const { AzureOpenAI } = require("openai");
+    
+    // Set the Azure and AI Search values from environment variables
+    const endpoint = process.env["AZURE_OPENAI_ENDPOINT"];
+    const apiKey = process.env["AZURE_OPENAI_API_KEY"];
+    const searchEndpoint = process.env["AZURE_AI_SEARCH_ENDPOINT"];
+    const searchKey = process.env["AZURE_AI_SEARCH_API_KEY"];
+    const searchIndex = process.env["AZURE_AI_SEARCH_INDEX"];
+    
+    // Required Azure OpenAI deployment name and API version
+    const deploymentName = "gpt-4";
+    const apiVersion = "2024-07-01-preview";
+    
+    function getClient() {
+      return new AzureOpenAI({
+        endpoint,
+        apiKey,
+        deployment: deploymentName,
+        apiVersion,
+      });
+    }
+    
+    async function main() {
+      const client = getClient();
+    
+      const messages = [
+        { role: "user", content: "What are my available health plans?" },
+      ];
+    
+      console.log(`Message: ${messages.map((m) => m.content).join("\n")}`);
+    
+      const events = await client.chat.completions.create({
+        stream: true,
+        messages: [
+          {
+            role: "user",
+            content:
+              "What's the most common feedback we received from our customers about the product?",
+          },
+        ],
+        max_tokens: 128,
+        model: "",
+        data_sources: [
+          {
+            type: "azure_search",
+            parameters: {
+              endpoint: searchEndpoint,
+              index_name: searchIndex,
+              authentication: {
+                type: "api_key",
+                key: searchKey,
+              },
+            },
+          },
+        ],
+      });
+    
+      let response = "";
+      for await (const event of events) {
+        for (const choice of event.choices) {
+          const newText = choice.delta?.content;
+          if (newText) {
+            response += newText;
+            // To see streaming results as they arrive, uncomment line below
+            // console.log(newText);
+          }
+        }
+      }
+      console.log(response);
+    }
+    
+    main().catch((err) => {
+      console.error("The sample encountered an error:", err);
+    });
+    ```
 
+1. Run the application with the following command:
 
+    ```console
+    node ChatWithOwnData.js
+    ```
 
-module.exports = { main };
-```
+---
 
 > [!IMPORTANT]
 > For production, use a secure way of storing and accessing your credentials like [Azure Key Vault](/azure/key-vault/general/overview). For more information about credential security, see the Azure AI services [security](../../security-features.md) article.
 
-```cmd
-node.exe ChatWithOwnData.js
-```
 
 ## Output
 

@@ -5,7 +5,7 @@ description: Use this article to import and use your data in Azure OpenAI.
 #services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
-ms.custom: devx-track-dotnet, devx-track-extended-java, devx-track-js, devx-track-go, devx-track-python
+ms.custom: devx-track-dotnet, devx-track-extended-java, devx-track-js, devx-track-ts, devx-track-go, devx-track-python
 ms.topic: quickstart
 author: aahill
 ms.author: aahi
@@ -24,7 +24,7 @@ zone_pivot_groups: openai-use-your-data
 
 ::: zone pivot="programming-language-javascript"
 
-[Reference](/javascript/api/@azure/openai) | [Source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/openai/openai) | [Package (npm)](https://www.npmjs.com/package/@azure/openai) | [Samples](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/openai/Azure.AI.OpenAI/tests/Samples)
+[Reference documentation](https://platform.openai.com/docs/api-reference/chat) | [Source code](https://github.com/openai/openai-node) | [Package (npm)](https://www.npmjs.com/package/openai) | [Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/openai/openai/samples)
 
 ::: zone-end
 
@@ -46,16 +46,35 @@ In this quickstart, you can use your own data with Azure OpenAI models. Using Az
 
 ## Prerequisites
 
+#### [TypeScript](#tab/typescript)
+
 - An Azure subscription - <a href="https://azure.microsoft.com/free/cognitive-services" target="_blank">Create one for free</a>.
 
+- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)
+- [TypeScript](https://www.typescriptlang.org/download/)
+
 - An Azure OpenAI resource deployed in a [supported region and with a supported model](./concepts/use-your-data.md#regional-availability-and-model-support).
 
-- Be sure that you are assigned at least the [Cognitive Services Contributor](./how-to/role-based-access-control.md#cognitive-services-contributor) role for the Azure OpenAI resource.
+- Be sure that you're assigned at least the [Cognitive Services Contributor](./how-to/role-based-access-control.md#cognitive-services-contributor) role for the Azure OpenAI resource.
 
 - Download the example data from [GitHub](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/openai/contoso_benefits_document_example.pdf) if you don't have your own data.
 
+#### [JavaScript](#tab/javascript)
+
+- An Azure subscription - <a href="https://azure.microsoft.com/free/cognitive-services" target="_blank">Create one for free</a>.
+- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)
+- An Azure OpenAI resource deployed in a [supported region and with a supported model](./concepts/use-your-data.md#regional-availability-and-model-support).
+
+- Be sure that you're assigned at least the [Cognitive Services Contributor](./how-to/role-based-access-control.md#cognitive-services-contributor) role for the Azure OpenAI resource.
+
+- Download the example data from [GitHub](https://github.com/Azure-Samples/cognitive-services-sample-data-files/blob/master/openai/contoso_benefits_document_example.pdf) if you don't have your own data.
+
+---
+
 ::: zone pivot="programming-language-javascript"
 
+
+
 - [Long Term Support (LTS) versions of Node.js](https://github.com/nodejs/release#release-schedule)
 
 ::: zone-end

@@ -42,7 +42,7 @@ Request access: [limited access model application](https://aka.ms/oai/modelacces
 
 ### Limitations
 
-The `o1-preview` and `o1-mini` models are currently in preview and do not include some features available in other models, such as image understanding and structured outputs found in the GPT-4o and GPT-4o-mini models. For many tasks, the generally available GPT-4o models may still be more suitable.
+The `o1` series models are currently in preview and do not include some features available in other models, such as image understanding and structured outputs which are available in the latest GPT-4o model. For many tasks, the generally available GPT-4o models may still be more suitable.
 
 ### Safety