Merge pull request #2675 from HeidiSteen/heidist-rag

Updates to add a vector index in Foundry portal

Author: prmerger-automator[bot]

articles/ai-studio/how-to/index-add.md

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: how-to
-ms.date: 12/11/2024
+ms.date: 01/31/2025
 ms.reviewer: estraight
 ms.author: ssalgado
 author: ssalgadodev
@@ -19,24 +19,26 @@ author: ssalgadodev
 
 [!INCLUDE [feature-preview](../includes/feature-preview.md)]
 
-In this article, you learn how to create and use a vector index for performing [Retrieval Augmented Generation (RAG)](../concepts/retrieval-augmented-generation.md).
+In this article, you learn how to create and use a vector index for performing [Retrieval Augmented Generation (RAG)](../concepts/retrieval-augmented-generation.md) in the Azure AI Foundry portal.
+
+A vector index isn't required for RAG, but a vector query can match on semantically similar content, which is useful for RAG workloads.
 
 ## Prerequisites
 
 You must have:
 - An Azure AI Foundry project
-- An Azure AI Search resource
+- An [Azure AI Search resource](/azure/search/search-create-service-portal)
+- You should have content in a supported format that provides sufficient information for a chat experience. It can be an existing index on Azure AI Search, or create a new index using content files in Azure Blob Storage, your local system, or data in Azure AI Foundry.
 
 ## Create an index from the Chat playground
 
 1. Sign in to [Azure AI Foundry](https://ai.azure.com).
 1. Go to your project or [create a new project](../how-to/create-projects.md) in Azure AI Foundry portal.
-1. From the menu on the left, select **Playgrounds**.
-
+1. From the menu on the left, select **Playgrounds**. Select the **Chat Playground**.
 
     :::image type="content" source="../media/index-retrieve/project-left-menu.png" alt-text="Screenshot of Project Left Menu." lightbox="../media/index-retrieve/project-left-menu.png":::
 
-1. Select a deployed model. If you have not done so already, deploy a model by selecting **Create new deployment**.
+1. Select a deployed chat completion model. If you have not done so already, deploy a model by selecting **Create new deployment**.
 
    :::image type="content" source="../media/index-retrieve/create-deployment.png" alt-text="Screenshot of create a deployment button." lightbox="../media/index-retrieve/create-deployment.png":::
 
@@ -46,11 +48,13 @@ You must have:
 
 1. Choose your **Source data**. You can choose source data from a list of your recent data sources, a storage URL on the cloud, or upload files and folders from the local machine. You can also add a connection to another data source such as Azure Blob Storage.
 
+   If you don't have sample data, you can [download these PDFs](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/health-plan) to your local system, and then upload them as your source data.
+
     :::image type="content" source="../media/index-retrieve/select-source-data.png" alt-text="Screenshot of select source data." lightbox="../media/index-retrieve/select-source-data.png":::
 
 1. Select **Next** after choosing source data
 1. Choose the **Index Storage** - the location where you want your index to be stored in the **Index configuration** tab. 
-1. If you already have an Azure AI Search resource, you can choose that from the dropdown.
+1. If you already have an Azure AI Search resource, you can browse the list of search service resources for your subscription and then select **Connect** for the one you want to use. If you're connecting with API keys, confirm your search service [uses API keys](/azure/search/search-security-api-keys).
 
     :::image type="content" source="../media/index-retrieve/index-storage.png" alt-text="Screenshot of select index store." lightbox="../media/index-retrieve/index-storage.png":::
 
@@ -62,7 +66,6 @@ You must have:
 1. Review the details you entered and select **Create**
 1. You're taken to the index details page where you can see the status of your index creation.
 
-
 ## Use an index in prompt flow
 
 1. Sign in to [Azure AI Foundry](https://ai.azure.com) and select your project.