@@ -210,6 +210,11 @@
             "redirect_url": "/azure/ai-foundry/model-inference/how-to/create-model-deployments",
             "redirect_document_id": false
           },
+          {
+            "source_path_from_root": "/articles/ai-studio/how-to/custom-policy-model-deployment.md",
+            "redirect_url": "/azure/ai-foundry/model-inference/how-to/configure-deployment-policies",
+            "redirect_document_id": true
+          },
           {
             "source_path_from_root": "/articles/ai-studio/ai-services/how-to/content-safety.md",
             "redirect_url": "/azure/ai-services/content-safety/how-to/foundry",

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: how-to
-ms.date: 11/19/2024
+ms.date: 2/12/2025
 ms.reviewer: eur
 ms.author: eur
 author: eric-urban
@@ -25,7 +25,7 @@ This article describes how to use new or existing Azure AI services resources in
 
 Depending on the AI service and model you want to use, you can use them in Azure AI Foundry portal via:
 - [Bring your existing Azure AI services resources](#bring-your-existing-azure-ai-services-resources-into-a-project) into a project. You can use your existing Azure AI services resources in an Azure AI Foundry project by creating a connection to the resource.
-- The [model catalog](#discover-azure-ai-models-in-the-model-catalog). You don't need a project to browse and discover Azure AI models. Some of the Azure AI services are available for you to try via the model catalog without a project. Some Azure AI services require a project to use in the playgrounds.
+- The [model catalog](#discover-azure-ai-models-in-the-model-catalog). You don't need a project to browse and discover Azure AI models. Some of the Azure AI services are available for you to try via the model catalog without a project. Some Azure AI services require a project to use them in the playgrounds.
 - The [project-level playgrounds](#try-azure-ai-services-in-the-project-level-playgrounds). You need a project to try Azure AI services such as Azure AI Speech and Azure AI Language. 
 - [Azure AI Services demo pages](#try-out-azure-ai-services-demos). You can browse Azure AI services capabilities and step through the demos. You can try some limited demos for free without a project.
 - [Fine-tune](#fine-tune-azure-ai-services-models) models. You can fine-tune a subset of Azure AI services models in Azure AI Foundry portal.
@@ -40,7 +40,7 @@ Let's look at two ways to connect Azure AI services resources to an Azure AI Fou
 
 ### Connect Azure AI services when you create a project for the first time
 
-When you create a project for the first time, you also create a hub. When you create a hub, you can select an existing Azure AI services resource (including Azure OpenAI) or create a new AI services resource.
+When you create a project for the first time, you can select an existing Azure AI services resource (including Azure OpenAI) or create a new AI services resource.
 
 :::image type="content" source="../../media/how-to/projects/projects-create-resource.png" alt-text="Screenshot of the create resource page within the create project dialog." lightbox="../../media/how-to/projects/projects-create-resource.png":::
 
@@ -58,7 +58,7 @@ To use your existing Azure AI services resources (such as Azure AI Speech) in an
 
     :::image type="content" source="../../media/ai-services/connections-add.png" alt-text="Screenshot of the connected resources page with the button to create a new connection." lightbox="../../media/ai-services/connections-add.png":::
 
-1. On the **Add a connection to external assets** page, select the kind of AI service that you want to connect to the project. For example, you can select Azure OpenAI Service, Azure AI Content Safety, Azure AI Speech, Azure AI Language, and other AI services.
+1. On the **Add a connection to external assets** page, select the kind of AI service that you want to connect to the project. For example, you can select Azure AI services (for a connection to multiple services in one resource), Azure OpenAI Service, Azure AI Content Safety, Azure AI Speech, Azure AI Language, and other AI services.
 
     :::image type="content" source="../../media/ai-services/connections-add-assets.png" alt-text="Screenshot of the page to select the kind of AI service that you want to connect to the project." lightbox="../../media/ai-services/connections-add-assets.png":::
 
@@ -72,7 +72,7 @@ To use your existing Azure AI services resources (such as Azure AI Speech) in an
 
 You can discover Azure AI models in the model catalog without a project. Some Azure AI services are available for you to try via the model catalog without a project. 
 
-1. Go to the [Azure AI Foundry home page](https://ai.azure.com).
+1. Go to the [Azure AI Foundry portal home page](https://ai.azure.com).
 1. Select the tile that says **Model catalog and benchmarks**. 
 
     :::image type="content" source="../../media/explore/ai-studio-home-model-catalog.png" alt-text="Screenshot of the home page in Azure AI Foundry portal with the option to select the model catalog tile." lightbox="../../media/explore/ai-studio-home-model-catalog.png":::
@@ -139,9 +139,9 @@ Once you have a project, several Azure AI services models are already deployed a
 1. Go to your Azure AI Foundry project.
 1. Select **Management center** from the left pane.
 1. Select **Models + endpoints** (under **Project**) from the left pane. 
-1. Select the **Service deployments** tab to view the list of Azure AI services models that are already deployed.
+1. Select the **Service endpoints** tab to view the list of Azure AI services models that are already deployed.
 
-    :::image type="content" source="../../media/ai-services/endpoint/models-endpoints-ai-services-deployments.png" alt-text="Screenshot of the models and endpoints page to view Azure AI services deployments." lightbox="../../media/ai-services/endpoint/models-endpoints-ai-services-deployments.png":::
+    :::image type="content" source="../../media/ai-services/endpoint/models-endpoints-ai-services-deployments.png" alt-text="Screenshot of the models and endpoints page to view Azure AI services endpoints." lightbox="../../media/ai-services/endpoint/models-endpoints-ai-services-deployments.png":::
 
     In this example, we see:
     - Six Azure AI Services deployments (such as Azure AI Speech and Azure AI Language) via the default connection. These models were already available for use when you created the project.
@@ -151,7 +151,6 @@ There's no option to deploy Azure AI services models from the **Models + endpoin
 
 However, you can deploy [fine-tuned Azure AI services models](#fine-tune-azure-ai-services-models). For example, you might want to deploy a custom speech model that you fine-tuned. In this case, you can deploy the model from the corresponding fine-tuning page. 
 
-
 ## Related content
 
 - [What are Azure AI services?](../../../ai-services/what-are-ai-services.md?context=/azure/ai-studio/context/context)

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: how-to
-ms.date: 11/19/2024
+ms.date: 2/12/2025
 ms.reviewer: eur
 ms.author: eur
 author: eric-urban
@@ -102,7 +102,7 @@ Here are a few guides to help you get started with Azure OpenAI Service playgrou
 - [Quickstart: Use GPT-4o in the real-time audio playground](../../../ai-services/openai/realtime-audio-quickstart.md?context=/azure/ai-studio/context/context)
 - [Quickstart: Analyze images and video with GPT-4 for Vision in the playground](../../quickstarts/multimodal-vision.md)
 
-Each playground has different model requirements and capabilities. The supported regions will vary depending on the model. For more information about model availability per region, see the [Azure OpenAI Service models documentation](../../../ai-services/openai/concepts/models.md).
+Each playground has different model requirements and capabilities. The supported regions vary depending on the model. For more information about model availability per region, see the [Azure OpenAI Service models documentation](../../../ai-services/openai/concepts/models.md).
 
 ## Fine-tune Azure OpenAI models
 

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: how-to
-ms.date: 11/19/2024
+ms.date: 02/12/2025
 ms.reviewer: larryfr
 ms.author: larryfr
 author: Blackmist
@@ -36,7 +36,7 @@ Here's a table of some of the available connection types in Azure AI Foundry por
 | Azure Content Safety | | Azure AI Content Safety is a service that detects potentially unsafe content in text, images, and videos. |
 | Azure OpenAI || Azure OpenAI is a service that provides access to OpenAI's models including the GPT-4o, GPT-4o mini, GPT-4, GPT-4 Turbo with Vision, GPT-3.5-Turbo, DALLE-3 and Embeddings model series with the security and enterprise capabilities of Azure. |
 | Serverless Model | ✓ | Serverless Model connections allow you to [serverless API deployment](deploy-models-serverless.md). |
-| Microsoft OneLake | | Microsoft OneLake provides open access to all of your Fabric items through Azure Data Lake Storage (ADLS) Gen2 APIs and SDKs.<br/><br/>In Azure AI Foundry portal you can set up a connection to your OneLake data using a OneLake URI. You can find the information that Azure AI Foundry requires to construct a __OneLake Artifact URL__ (workspace and item GUIDs) in the URL on the Fabric portal. For information about the URI syntax, see [Connecting to Microsoft OneLake](/fabric/onelake/onelake-access-api). |
+| Microsoft OneLake | | Microsoft OneLake provides open access to all of your Fabric items through Azure Data Lake Storage (ADLS) Gen2 APIs and SDKs.<br/><br/>In Azure AI Foundry portal, you can set up a connection to your OneLake data using a OneLake URI. You can find the information that Azure AI Foundry requires to construct a __OneLake Artifact URL__ (workspace and item GUIDs) in the URL on the Fabric portal. For information about the URI syntax, see [Connecting to Microsoft OneLake](/fabric/onelake/onelake-access-api). |
 | API key || API Key connections handle authentication to your specified target on an individual basis. For example, you can use this connection with the SerpApi tool in prompt flow.  |
 | Custom || Custom connections allow you to securely store and access keys while storing related properties, such as targets and versions. Custom connections are useful when you have many targets that or cases where you wouldn't need a credential to access. LangChain scenarios are a good example where you would use custom service connections. Custom connections don't manage authentication, so you have to manage authentication on your own. |
 
@@ -58,7 +58,7 @@ Follow these steps to create a new connection that's only available for the curr
 1. Browse for and select your Azure AI Search service from the list of available services and then select the type of __Authentication__ to use for the resource. Select __Add connection__.
 
     > [!TIP]
-    > Different connection types support different authentication methods. Using Microsoft Entra ID may require specific Azure role-based access permissions for your developers. For more information, visit [Role-based access control](../concepts/rbac-ai-studio.md#scenario-connections-using-microsoft-entra-id-authentication).
+    > Different connection types support different authentication methods. Using Microsoft Entra ID might require specific Azure role-based access permissions for your developers. For more information, visit [Role-based access control](../concepts/rbac-ai-studio.md#scenario-connections-using-microsoft-entra-id-authentication).
 
     :::image type="content" source="../media/data-connections/connection-add-azure-ai-search-connect-entra-id.png" alt-text="Screenshot of the page to select the Azure AI Search service that you want to connect to." lightbox="../media/data-connections/connection-add-azure-ai-search-connect-entra-id.png":::
 

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: how-to
-ms.date: 11/19/2024
+ms.date: 02/12/2025
 ms.reviewer: deeikele
 ms.author: larryfr
 author: Blackmist
@@ -99,10 +99,10 @@ At hub creation, select between the networking isolation modes: **Public**, **Pr
 
 At hub creation in the Azure portal, creation of associated Azure AI services, Storage account, Key vault (optional), Application insights (optional), and Container registry (optional) is given. These resources are found on the Resources tab during creation. 
 
-To connect to Azure AI services (Azure OpenAI, Azure AI Search, and Azure AI Content Safety) or storage accounts in Azure AI Foundry portal, create a private endpoint in your virtual network. Ensure the public network access (PNA) flag is disabled when creating the private endpoint connection. For more about Azure AI services connections, follow documentation [here](../../ai-services/cognitive-services-virtual-networks.md). You can optionally bring your own (BYO) search, but this requires a private endpoint connection from your virtual network.
+To connect to Azure AI services (Azure OpenAI, Azure AI Search, and Azure AI Content Safety) or storage accounts in Azure AI Foundry portal, create a private endpoint in your virtual network. Ensure the public network access (PNA) flag is disabled when creating the private endpoint connection. For more about Azure AI services connections, see [Virtual networks for Azure AI Services](../../ai-services/cognitive-services-virtual-networks.md). You can optionally bring your own Azure AI Search, but it requires a private endpoint connection from your virtual network.
 
 ### Encryption
-Projects that use the same hub, share their encryption configuration. Encryption mode can be set only at the time of hub creation between Microsoft-managed keys and Customer-managed keys. 
+Projects that use the same hub, share their encryption configuration. Encryption mode can be set only at the time of hub creation between Microsoft-managed keys and Customer-managed keys (CMK). 
 
 From the Azure portal view, navigate to the encryption tab, to find the encryption settings for your hub. 
 For hubs that use CMK encryption mode, you can update the encryption key to a new key version. This update operation is constrained to keys and key versions within the same Key Vault instance as the original key.
@@ -111,7 +111,7 @@ For hubs that use CMK encryption mode, you can update the encryption key to a ne
 
 ### Update Azure Application Insights and Azure Container Registry
 
-To use custom environments for Prompt Flow, you're required to configure an Azure Container Registry for your hub. To use Azure Application Insights for Prompt Flow deployments, a configured Azure Application Insights resource is required for your hub. Updating the workspace-attached Azure Container Registry or Application Insights resources may break lineage of previous jobs, deployed inference endpoints, or your ability to rerun earlier jobs in the workspace. After association with an Azure AI Foundry hub, Azure Container Registry and Application Insights resources cannot be disassociated (set to null).
+To use custom environments for Prompt Flow, you're required to configure an Azure Container Registry for your hub. To use Azure Application Insights for Prompt Flow deployments, a configured Azure Application Insights resource is required for your hub. Updating the workspace-attached Azure Container Registry or Application Insights resources might break lineage of previous jobs, deployed inference endpoints, or your ability to rerun earlier jobs in the workspace. After association with an Azure AI Foundry hub, Azure Container Registry and Application Insights resources can't be disassociated (set to null).
 
 You can use the Azure portal, Azure SDK/CLI options, or the infrastructure-as-code templates to update both Azure Application Insights and Azure Container Registry for the hub.
 
@@ -152,15 +152,15 @@ az ml workspace update -n "myexamplehub" -g "{MY_RESOURCE_GROUP}" -a "APPLICATIO
 
 ### Choose how credentials are stored
 
-Select scenarios in Azure AI Foundry portal store credentials on your behalf. For example when you create a connection in Azure AI Foundry portal to access an Azure Storage account with stored account key, access Azure Container Registry with admin password, or when you create a compute instance with enabled SSH keys. No credentials are stored with connections when you choose Microsoft Entra ID identity-based authentication.
+Select scenarios in Azure AI Foundry portal store credentials on your behalf. For example, when you create a connection in Azure AI Foundry portal to access an Azure Storage account with stored account key, access Azure Container Registry with admin password, or when you create a compute instance with enabled SSH keys. No credentials are stored with connections when you choose Microsoft Entra ID identity-based authentication.
 
 You can choose where credentials are stored:
 
-- **Your Azure Key Vault**: This requires you to manage your own Azure Key Vault instance and configure it per hub. It gives you additional control over secret lifecycle e.g. to set expiry policies. You can also share stored secrets with other applications in Azure.
+- **Your Azure Key Vault**: This requires you to manage your own Azure Key Vault instance and configure it per hub. It gives you more control over secret lifecycle, for example, to set expiry policies. You can also share stored secrets with other applications in Azure.
    
-- **Microsoft-managed credential store (preview)**: In this variant Microsoft manages an Azure Key Vault instance on your behalf per hub. No resource management is needed on your side and the vault does not show in your Azure subscription. Secret data lifecycle follows the resource lifecycle of your hubs and projects. For example, when a project's storage connection is deleted, its stored secret is deleted as well.
+- **Microsoft-managed credential store (preview)**: In this variant Microsoft manages an Azure Key Vault instance on your behalf per hub. No resource management is needed on your side and the vault doesn't show in your Azure subscription. Secret data lifecycle follows the resource lifecycle of your hubs and projects. For example, when a project's storage connection is deleted, its stored secret is deleted as well.
 
-After your hub is created, it is not possible to switch between Your Azure Key Vault and using a Microsoft-managed credential store.
+After your hub is created, it isn't possible to switch between Your Azure Key Vault and using a Microsoft-managed credential store.
 
 ## Delete an Azure AI Foundry hub
 

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: how-to
-ms.date: 11/07/2024
+ms.date: 02/12/2025
 ms.reviewer: lochen
 ms.author: sgilley
 author: sdgilley
@@ -80,7 +80,7 @@ To manage a compute session, select the **Compute session running** on the top t
 - **Install packages from requirements.txt** Opens `requirements.txt` in prompt flow UI so you can add packages.
 - **View installed packages** shows the packages that are installed in the compute session. It includes the packages baked into base image and packages specified in the `requirements.txt` file in the flow folder.
 - **Reset compute session** deletes the current compute session and creates a new one with the same environment. If you encounter a package conflict, you can try this option.
-- **Stop compute session** deletes the current compute session. If there's no active compute session on an underlying serverless compute, the compute resource is also deleted. If the compute session is on a compute instance, stopping the session will allow the instance to become idle.
+- **Stop compute session** deletes the current compute session. If there's no active compute session on an underlying serverless compute, the compute resource is also deleted. If the compute session is on a compute instance, stopping the session allows the instance to become idle.
 
 :::image type="content" source="../media/prompt-flow/how-to-create-manage-compute-session/compute-session-create-automatic-actions.png" alt-text="Screenshot of actions for a compute session on a flow page." lightbox = "../media/prompt-flow/how-to-create-manage-compute-session/compute-session-create-automatic-actions.png":::
 
@@ -94,7 +94,7 @@ You can customize the environment that you use to run this flow by adding packag
 > [!NOTE]
 > You can change the location and even the file name of `requirements.txt`, but be sure to also change it in the `flow.dag.yaml` file in the flow folder.
 >
-> Don't pin the version of `promptflow` and `promptflow-tools` in `requirements.txt`, because they are already included in the compute session base image.
+> Don't pin the version of `promptflow` and `promptflow-tools` in `requirements.txt`, because they're already included in the compute session base image.
 
 ### Add packages in a private feed in Azure DevOps
 
@@ -140,7 +140,7 @@ By default, we use the latest prompt flow image as the base image. If you want t
 
 If you previously created a compute instance runtime, switch it to a compute session by using the following steps:
 
-- Prepare your `requirements.txt` file in the flow folder. See [Manage a compute session](#manage-a-compute-session) for more information.
+- Prepare your `requirements.txt` file in the flow folder. For more information, see [Manage a compute session](#manage-a-compute-session).
 - If you created a custom environment, get the image from the environment detail page, and specify it in the `flow.dag.yaml` file in the flow folder. To learn more, see [Change the base image](#change-the-base-image). Make sure you have `acr pull` permission for the image.
 
 - You can continue to use the existing compute instance if you would like to manually manage the lifecycle.

@@ -1143,7 +1143,7 @@ Quota is managed per deployment. Each deployment has a rate limit of 200,000 tok
 
 ## Related content
 
-
+* [Explore DeepSeek-related Azure samples in various languages](https://github.com/azure-samples/deepseek)
 * [Azure AI Model Inference API](../reference/reference-model-inference-api.md)
 * [Deploy models as serverless APIs](deploy-models-serverless.md)
 * [Consume serverless API endpoints from a different Azure AI Studio project or hub](deploy-models-serverless-connect.md)

@@ -6,7 +6,7 @@ ms.reviewer: sgilley
 ms.author: sgilley
 ms.service: azure-ai-foundry
 ms.topic: include
-ms.date: 10/29/2024
+ms.date: 02/12/2025
 ms.custom: include, ignite-2024
 ---
 
@@ -19,7 +19,7 @@ To work with a model, you first deploy it into a project. If you don't yet have
   
         :::image type="content" source="../media/tutorials/chat/home-page.png" alt-text="Screenshot of the home page if with no projects." lightbox="../media/tutorials/chat/home-page.png":::
 
-    * If you have projects but aren't in one, select the project you wish to use, then select **Model catalog** from the left navigation pane. Or, you can select **Model catalog and benchmarks** at the bottom of the screen.
+    * If you have projects but aren't in one, select the project you wish to use, then select **Model catalog** from the left navigation pane.
     * If you are in a project, select **Model catalog** from the left navigation pane.
 
 1. Select the **gpt-4o-mini** model from the list of models. You can use the search bar to find it. 
@@ -38,4 +38,4 @@ To work with a model, you first deploy it into a project. If you don't yet have
         1. Provide a name for your project.
         1. Select **Create a project**.
 
-1. Leave the default **Deployment name**. Select **Connect and deploy**.
+1. Leave the default **Deployment name**. Select **Deploy**.

@@ -6,7 +6,7 @@ manager: scottpolly
 ms.service: azure-ai-foundry
 ms.custom: build-2024, devx-track-azurecli, devx-track-python, ignite-2024
 ms.topic: how-to
-ms.date: 11/07/2024
+ms.date: 02/12/2025
 ms.reviewer: dantaylo
 ms.author: sgilley
 author: sdgilley

@@ -8,7 +8,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: quickstart
-ms.date: 10/22/2024
+ms.date: 02/12/2025
 ms.reviewer: zuramir
 ms.author: sgilley
 author: sdgilley
@@ -38,7 +38,7 @@ If you don't have an Azure subscription, <a href="https://azure.microsoft.com/fr
 
 7. Once the model is deployed, select **Open in playground** to test your model.
 
-You're now in a project, with a deployed model.  You can use the chat playground to interact with your model.
+You're now in a project, with a deployed model. You can use the chat playground to interact with your model.
 
 For more information about deploying models, see [how to deploy models](../how-to/deploy-models-openai.md).
 

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: quickstart
-ms.date: 11/19/2024
+ms.date: 2/12/2025
 ms.reviewer: eur
 ms.author: eur
 author: eric-urban
@@ -36,7 +36,7 @@ The speech to text and text to speech features can be used together or separatel
 
 Before you can start a chat session, you need to configure the chat playground to use the speech to text and text to speech features.
 
-1. Sign in to [Azure AI Foundry](https://ai.azure.com).
+1. Sign in to the [Azure AI Foundry portal](https://ai.azure.com).
 1. Go to your Azure AI Foundry project. If you need to create a project, see [Create an Azure AI Foundry project](../how-to/create-projects.md).
 1. Select **Playgrounds** from the left pane and then select a playground to use. In this example, select **Try the chat playground**.
 1. Select your deployed chat model from the **Deployment** dropdown. 
@@ -48,9 +48,9 @@ Before you can start a chat session, you need to configure the chat playground t
     :::image type="content" source="../media/quickstarts/hear-speak/playground-settings-select.png" alt-text="Screenshot of the chat playground with options to get to the chat capabilities settings." lightbox="../media/quickstarts/hear-speak/playground-settings-select.png":::
 
     > [!NOTE]
-    > You should also see the options to select the microphone or speaker buttons. If you select either of these buttons, but haven't yet enabled speech to text or text to speech, you are prompted to enable them in **Chat capabilities**. 
+    > You should also see the options to select the microphone or speaker buttons. If you select either of these buttons, but didn't yet enable speech to text or text to speech, you're prompted to enable them in **Chat capabilities**. 
 
-1. On the **Chat capabilities** page, select the box to acknowledge that usage of the speech feature will incur additional costs. For more information, see [Azure AI Speech pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/).
+1. On the **Chat capabilities** page, select the box to acknowledge that usage of the speech feature incurs extra costs. For more information, see [Azure AI Speech pricing](https://azure.microsoft.com/pricing/details/cognitive-services/speech-services/).
 
 1. Select **Enable speech to text** and **Enable text to speech**.  
 
@@ -67,7 +67,7 @@ Before you can start a chat session, you need to configure the chat playground t
 
 In this chat session, you use both speech to text and text to speech. You use the speech to text feature to speak to the assistant, and the text to speech feature to hear the assistant's response. 
 
-1. Complete the steps in the [Configure the playground](#configure-the-chat-playground) section if you haven't already done so. To complete this quickstart you need to enable the speech to text and text to speech features.
+1. Complete the steps in the [Configure the playground](#configure-the-chat-playground) section. To complete this quickstart, you need to enable the speech to text and text to speech features.
 1. Select the microphone button and speak to the assistant. For example, you can say "Do you know where I can get an Xbox".
 
     :::image type="content" source="../media/quickstarts/hear-speak/chat-session-speaking.png" alt-text="Screenshot of the chat session with the enabled microphone icon and send button highlighted." lightbox="../media/quickstarts/hear-speak/chat-session-speaking.png":::
@@ -76,7 +76,7 @@ In this chat session, you use both speech to text and text to speech. You use th
 1. Select the send button (right arrow) to send your message to the assistant. The assistant's response is displayed in the chat session pane.
 
     > [!NOTE]
-    > If the speaker button is turned on, you'll hear the assistant's response. If the speaker button is turned off, you won't hear the assistant's response, but the response will still be displayed in the chat session pane.
+    > If the speaker button is turned on, you hear the assistant's response. If the speaker button is turned off, you don't hear the assistant's response, but the response is still displayed in the chat session pane.
 
 1. You can change the system prompt to change the assistant's response format or style. 
 

@@ -405,7 +405,7 @@ items:
     - name: Built-in policy to allow specific models
       href: how-to/built-in-policy-model-deployment.md
     - name: Custom policy to allow specific models
-      href: how-to/custom-policy-model-deployment.md
+      href: ../ai-foundry/model-inference/how-to/configure-deployment-policies.md?context=/azure/ai-studio/context/context
   - name: Vulnerability management
     href: concepts/vulnerability-management.md
   - name: Disaster recovery

@@ -5,7 +5,7 @@ description:  Learn how to build a RAG-based chat app using the Azure AI Foundry
 manager: scottpolly
 ms.service: azure-ai-foundry
 ms.topic: tutorial
-ms.date: 12/18/2024
+ms.date: 02/12/2025
 ms.reviewer: lebaro
 ms.author: sgilley
 author: sdgilley
@@ -78,11 +78,6 @@ The search index is used to store vectorized data from the embeddings model. The
     python create_search_index.py
     ```
 
-1. Once the script is run, you can view your newly created index in the **Data + indexes** page of your Azure AI Foundry project. For more information, see [How to build and consume vector indexes in Azure AI Foundry portal](../how-to/index-add.md).
-
-1. If you run the script again with the same index name, it creates a new version of the same index.
-
-
 ## <a name="get-documents"></a> Get product documents
 
 Next, you create a script to get product documents from the search index. The script queries the search index for documents that match a user's question.
@@ -176,6 +171,7 @@ To enable logging of telemetry to your project:
    python chat_with_products.py --query "I need a new tent for 4 people, what would you recommend?" --enable-telemetry 
    ```
 
+Follow the link in the console output to see the telemetry data in your Application Insights resource. If it doesn't appear right away, wait a few minutes and select **Refresh** in the toolbar.
 
 ## Clean up resources
 

@@ -7,7 +7,7 @@ ms.service: azure-ai-foundry
 ms.custom:
   - ignite-2024
 ms.topic: tutorial
-ms.date: 12/18/2024
+ms.date: 02/12/2025
 ms.reviewer: lebaro
 ms.author: sgilley
 author: sdgilley

@@ -85,7 +85,7 @@ In Part 1 of this tutorial series, you created an **.env** file that specifies t
 1. In your project in Azure AI Foundry portal, select **Models + endpoints**.
 1. Select **gpt-4o-mini**.  
 1. Select **Edit**.
-1. If you have quota to increase the **Tokens per Minute Rate Limit**, try increasing it to 30. 
+1. If you have quota to increase the **Tokens per Minute Rate Limit**, try increasing it to 30 or above. 
 1. Select **Save and close**.
 
 ### Run the evaluation script
@@ -108,6 +108,8 @@ In Part 1 of this tutorial series, you created an **.env** file that specifies t
     python evaluate.py
     ```
 
+Expect the evaluation to take a few minutes to complete.
+
 ### Interpret the evaluation output
 
 In the console output, you see an answer for each question, followed by a table with summarized metrics. (You might see different columns in your output.)
@@ -160,7 +162,7 @@ For more information about evaluation results in Azure AI Foundry portal, see [H
 
 Notice that the responses are not well grounded. In many cases, the model replies with a question rather than an answer. This is a result of the prompt template instructions. 
  
-* In your **assets/grounded_chat.prompty** file, find the sentence "If the question is related to outdoor/camping gear and clothing but vague, ask for clarifying questions instead of referencing documents."
+* In your **assets/grounded_chat.prompty** file, find the sentence "If the question is not related to outdoor/camping gear and clothing, just say 'Sorry, I only can answer queries related to outdoor/camping gear and clothing. So, how can I help?'"
 * Change the sentence to "If the question is related to outdoor/camping gear and clothing but vague, try to answer based on the reference documents, then ask for clarifying questions."  
 * Save the file and re-run the evaluation script.