more fixes

msakande · msakande · commit 5f40744acbbe · 2025-05-11T15:13:19.000-05:00
diff --git a/articles/ai-foundry/how-to/develop/trace-local-sdk.md b/articles/ai-foundry/how-to/develop/trace-local-sdk.md
@@ -24,7 +24,7 @@ In this article, you'll learn how to trace your application with Azure AI Foundr
 
 - An [Azure Subscription](https://azure.microsoft.com/).
 - An Azure AI project, see [Create a project in Azure AI Foundry portal](../create-projects.md).
-- An AI model supporting the [Azure AI model inference API](https://aka.ms/azureai/modelinference) deployed through Azure AI Foundry.
+- An AI model supporting the [Azure AI Foundry Models API](https://aka.ms/azureai/modelinference) deployed through Azure AI Foundry.
 - If using Python, you need Python 3.8 or later installed, including pip.
 - If using JavaScript, the supported environments are LTS versions of Node.js.
 
diff --git a/articles/ai-foundry/model-inference/how-to/quickstart-ai-project.md b/articles/ai-foundry/model-inference/how-to/quickstart-ai-project.md
@@ -1,7 +1,7 @@
 ---
 title: Configure your AI project to use Azure AI Foundry Models
 titleSuffix: Azure AI Foundry
-description: Learn how to upgrade your AI project to use models deployed in Azure AI Foundry Models in Azure AI Foundry
+description: Learn how to upgrade your AI project to use models deployed in Azure AI Foundry Models in Azure AI Foundry Service
 ms.service: azure-ai-model-inference
 ms.topic: how-to
 ms.date: 1/21/2025
@@ -26,13 +26,13 @@ Additionally, deploying models to Azure AI Foundry Models brings the extra benef
 > * Global capacity deployment type.
 > * [Key-less authentication](configure-entra-id.md) with role-based access control.
 
-In this article, you learn how to configure your project to use models deployed in Azure AI model inference in Azure AI services.
+In this article, you learn how to configure your project to use Foundry Models deployments.
 
 ## Prerequisites
 
 To complete this tutorial, you need:
 
-* An Azure subscription. If you're using [GitHub Models](https://docs.github.com/en/github-models/), you can upgrade your experience and create an Azure subscription in the process. Read [Upgrade from GitHub Models to Azure AI model inference](quickstart-github-models.md) if it's your case.
+* An Azure subscription. If you're using [GitHub Models](https://docs.github.com/en/github-models/), you can upgrade your experience and create an Azure subscription in the process. Read [Upgrade from GitHub Models to Foundry Models](quickstart-github-models.md) if it's your case.
 
 * An Azure AI services resource. For more information, see [Create an Azure AI Services resource](../../../ai-services/multi-service-resource.md??context=/azure/ai-services/model-inference/context/context).
 
@@ -42,9 +42,9 @@ To complete this tutorial, you need:
     > When your AI hub is provisioned, an Azure AI services resource is created with it and the two resources connected. To see which Azure AI services resource is connected to your project, go to the [Azure AI Foundry portal](https://ai.azure.com) > **Management center** > **Connected resources**, and find the connections of type **AI Services**. 
 
 
-## Configure the project to use Azure AI model inference
+## Configure the project to use Foundry Models
 
-To configure the project to use the Azure AI model inference capability in Azure AI Services, follow these steps:
+To configure the project to use the Foundry Models capability in Azure AI Foundry Services, follow these steps:
 
 1. Go to [Azure AI Foundry portal](https://ai.azure.com).
 
@@ -74,19 +74,19 @@ To configure the project to use the Azure AI model inference capability in Azure
 
    7. Return to the project's landing page to continue and now select the new created connection. Refresh the page if it doesn't show up immediately. 
 
-4. Under **Included capabilities**, ensure you select **Azure AI Inference**. The **Azure AI model inference endpoint** URI is displayed along with the credentials to get access to it.
+4. Under **Included capabilities**, ensure you select **Azure AI Inference**. The **Foundry Models endpoint** URI is displayed along with the credentials to get access to it.
 
     :::image type="content" source="../media/quickstart-ai-project/overview-endpoint-and-key.png" alt-text="Screenshot of the landing page for the project, highlighting the location of the connected resource and the associated inference endpoint." lightbox="../media/quickstart-ai-project/overview-endpoint-and-key.png":::
 
     > [!TIP]
-    > Each Azure AI services resource has a single **Azure AI model inference endpoint** which can be used to access any model deployment on it. The same endpoint serves multiple models depending on which ones are configured. Learn about [how the endpoint works](../concepts/endpoints.md#azure-ai-inference-endpoint).
+    > Each Azure AI Foundry Services resource has a single **Foundry Models endpoint** which can be used to access any model deployment on it. The same endpoint serves multiple models depending on which ones are configured. Learn about [how the endpoint works](../concepts/endpoints.md#azure-ai-inference-endpoint).
 
 5. Take note of the endpoint URL and credentials.
 
 
-### Create the model deployment in Azure AI model inference
+### Create the model deployment in Foundry Models
 
-For each model you want to deploy under Azure AI model inference, follow these steps:
+For each model you want to deploy under Foundry Models, follow these steps:
 
 1. Go to **Model catalog** section in [Azure AI Foundry portal](https://ai.azure.com/explore/models).
 
@@ -110,7 +110,7 @@ For each model you want to deploy under Azure AI model inference, follow these s
 
 8. Select **Deploy**.
 
-9. Once the deployment finishes, you see the endpoint URL and credentials to get access to the model. Notice that now the provided URL and credentials are the same as displayed in the landing page of the project for the **Azure AI model inference endpoint**.
+9. Once the deployment finishes, you see the endpoint URL and credentials to get access to the model. Notice that now the provided URL and credentials are the same as displayed in the landing page of the project for the **Foundry Models endpoint**.
 
 10. You can view all the models available under the resource by going to **Models + endpoints** section and locating the group for the connection to your AI Services resource:
 
@@ -139,11 +139,11 @@ Generate your first chat completion:
 Use the parameter `model="<deployment-name>` to route your request to this deployment. *Deployments work as an alias of a given model under certain configurations*. See [Routing](../concepts/endpoints.md#routing) concept page to learn how Azure AI Services route deployments.
 
 
-## Move from Serverless API Endpoints to Azure AI model inference
+## Move from Serverless API Endpoints to Foundry Models
 
-Although you configured the project to use the Azure AI model inference, existing model deployments continue to exist within the project as Serverless API Endpoints. Those deployments aren't moved for you. Hence, you can progressively upgrade any existing code that reference previous model deployments. To start moving the model deployments, we recommend the following workflow:
+Although you configured the project to use Foundry Models, existing model deployments continue to exist within the project as Serverless API Endpoints. Those deployments aren't moved for you. Hence, you can progressively upgrade any existing code that reference previous model deployments. To start moving the model deployments, we recommend the following workflow:
 
-1. Recreate the model deployment in Azure AI model inference. This model deployment is accessible under the **Azure AI model inference endpoint**.
+1. Recreate the model deployment in Foundry Models. This model deployment is accessible under the **Foundry Models endpoint**.
 
 2. Upgrade your code to use the new endpoint.
 
@@ -152,11 +152,11 @@ Although you configured the project to use the Azure AI model inference, existin
 
 ### Upgrade your code with the new endpoint
 
-Once the models are deployed under Azure AI Services, you can upgrade your code to use the Azure AI model inference endpoint. The main difference between how Serverless API endpoints and Azure AI model inference works reside in the endpoint URL and model parameter. While Serverless API Endpoints have a set of URI and key per each model deployment, Azure AI model inference has only one for all of them.
+Once the models are deployed under Azure AI Foundry Services, you can upgrade your code to use the Foundry Models endpoint. The main difference between how Serverless API endpoints and Foundry Models works reside in the endpoint URL and model parameter. While Serverless API Endpoints have a set of URI and key per each model deployment, Foundry Models has only one for all of them.
 
 The following table summarizes the changes you have to introduce:
 
-| Property | Serverless API Endpoints | Azure AI Model Inference |
+| Property | Serverless API Endpoints | Foundry Models |
 | -------- | ------------------------ | ------------------------ |
 | Endpoint      | `https://<endpoint-name>.<region>.inference.ai.azure.com` | `https://<ai-resource>.services.ai.azure.com/models` |
 | Credentials | One per model/endpoint. | One per Azure AI Services resource. You can use Microsoft Entra ID too. |
@@ -186,10 +186,10 @@ For each model deployed as Serverless API Endpoints, follow these steps:
 
 ## Limitations
 
-Consider the following limitations when configuring your project to use Azure AI model inference:
+Consider the following limitations when configuring your project to use Foundry Models:
 
-* Only models supporting pay-as-you-go billing (Models as a Service) are available for deployment to Azure AI model inference. Models requiring compute quota from your subscription (Managed Compute), including custom models, can only be deployed within a given project as Managed Online Endpoints and continue to be accessible using their own set of endpoint URI and credentials.
-* Models available as both pay-as-you-go billing and managed compute offerings are, by default, deployed to Azure AI model inference in Azure AI services resources. Azure AI Foundry portal doesn't offer a way to deploy them to Managed Online Endpoints. You have to turn off the feature mentioned at [Configure the project to use Azure AI model inference](#configure-the-project-to-use-azure-ai-model-inference) or use the Azure CLI/Azure ML SDK/ARM templates to perform the deployment.
+* Only models supporting pay-as-you-go billing (Models as a Service) are available for deployment to Foundry Models. Models requiring compute quota from your subscription (Managed Compute), including custom models, can only be deployed within a given project as Managed Online Endpoints and continue to be accessible using their own set of endpoint URI and credentials.
+* Models available as both pay-as-you-go billing and managed compute offerings are, by default, deployed to Foundry Models in Azure AI Foundry Services resources. Azure AI Foundry portal doesn't offer a way to deploy them to Managed Online Endpoints. You have to turn off the feature mentioned at [Configure the project to use Foundry Models](#configure-the-project-to-use-azure-ai-model-inference) or use the Azure CLI/Azure ML SDK/ARM templates to perform the deployment.
 
 ## Next steps
 
diff --git a/articles/ai-foundry/model-inference/how-to/use-blocklists.md b/articles/ai-foundry/model-inference/how-to/use-blocklists.md
@@ -1,7 +1,7 @@
 ---
-title: 'How to use blocklists with Azure AI model inference service in Azure AI services'
+title: 'How to use blocklists with Azure AI Foundry Models in Azure AI Foundry Service'
 titleSuffix: Azure AI Foundry
-description: Learn how to use blocklists with Azure AI model inference service in Azure AI services
+description: Learn how to use blocklists with Foundry Models in Azure AI Foundry Service.
 manager: nitinme
 ms.service: azure-ai-model-inference
 ms.topic: how-to
@@ -11,19 +11,19 @@ ms.author: fasantia
 ms.custom: ignite-2024, github-universe-2024
 ---
 
-# How to use blocklists with Azure AI model inference service in Azure AI services
+# How to use blocklists with Foundry Models in Azure AI Foundry services
 
 The configurable content filters are sufficient for most content moderation needs. However, you may need to filter terms specific to your use case. 
 
 ## Prerequisites
 
-* An Azure subscription. If you're using [GitHub Models](https://docs.github.com/en/github-models/), you can upgrade your experience and create an Azure subscription in the process. Read [Upgrade from GitHub Models to Azure AI model inference](quickstart-github-models.md) if it's your case.
+* An Azure subscription. If you're using [GitHub Models](https://docs.github.com/en/github-models/), you can upgrade your experience and create an Azure subscription in the process. Read [Upgrade from GitHub Models to Foundry Models](quickstart-github-models.md) if it's your case.
 
-* An Azure AI services resource. For more information, see [Create an Azure AI Services resource](../../../ai-services/multi-service-resource.md?context=/azure/ai-services/model-inference/context/context).
+* An Azure AI Foundry services resource. For more information, see [Create an Azure AI Foundry Services resource](../../../ai-services/multi-service-resource.md?context=/azure/ai-services/model-inference/context/context).
 
-* An Azure AI Foundry project [connected to your Azure AI services resource](configure-project-connection.md).
+* An Azure AI Foundry project [connected to your Azure AI Foundry services resource](configure-project-connection.md).
 
-* A model deployment. See [Add and configure models to Azure AI services](create-model-deployments.md) for adding models to your resource.
+* A model deployment. See [Add and configure models to Azure AI Foundry services](create-model-deployments.md) for adding models to your resource.
 
     > [!NOTE]
     > Blocklist (preview) is only supported for Azure OpenAI models.
diff --git a/articles/ai-foundry/model-inference/how-to/use-chat-completions.md b/articles/ai-foundry/model-inference/how-to/use-chat-completions.md
@@ -51,4 +51,4 @@ zone_pivot_groups: azure-ai-inference-samples
 * [Use embeddings models](use-embeddings.md)
 * [Use image embeddings models](use-image-embeddings.md)
 * [Use reasoning models](use-chat-reasoning.md)
-* [Azure AI Model Inference API](.././reference/reference-model-inference-api.md)
+* [Azure AI Foundry Models API](.././reference/reference-model-inference-api.md)
diff --git a/articles/ai-foundry/model-inference/how-to/use-chat-multi-modal.md b/articles/ai-foundry/model-inference/how-to/use-chat-multi-modal.md
@@ -51,4 +51,4 @@ zone_pivot_groups: azure-ai-inference-samples
 * [Use embeddings models](use-embeddings.md)
 * [Use image embeddings models](use-image-embeddings.md)
 * [Use reasoning models](use-chat-reasoning.md)
-* [Azure AI Model Inference API](.././reference/reference-model-inference-api.md)
+* [Azure AI Foundry Models API](.././reference/reference-model-inference-api.md)
diff --git a/articles/ai-foundry/model-inference/how-to/use-chat-reasoning.md b/articles/ai-foundry/model-inference/how-to/use-chat-reasoning.md
@@ -50,4 +50,4 @@ zone_pivot_groups: azure-ai-inference-samples
 
 * [Use embeddings models](use-embeddings.md)
 * [Use image embeddings models](use-image-embeddings.md)
-* [Azure AI Model Inference API](.././reference/reference-model-inference-api.md)
+* [Azure AI Foundry Models API](.././reference/reference-model-inference-api.md)
diff --git a/articles/ai-foundry/model-inference/how-to/use-embeddings.md b/articles/ai-foundry/model-inference/how-to/use-embeddings.md
@@ -49,4 +49,4 @@ zone_pivot_groups: azure-ai-inference-samples
 ## Related content
 
 * [Use image embeddings models](use-image-embeddings.md)
-* [Azure AI Model Inference API](.././reference/reference-model-inference-api.md)
+* [Azure AI Foundry Models API](.././reference/reference-model-inference-api.md)
diff --git a/articles/ai-foundry/model-inference/how-to/use-image-embeddings.md b/articles/ai-foundry/model-inference/how-to/use-image-embeddings.md
@@ -49,4 +49,4 @@ zone_pivot_groups: azure-ai-inference-samples
 ## Related content
 
 * [Use embeddings models](use-embeddings.md)
-* [Azure AI Model Inference API](.././reference/reference-model-inference-api.md)
+* [Azure AI Foundry Models API](.././reference/reference-model-inference-api.md)
diff --git a/articles/ai-foundry/model-inference/how-to/use-structured-outputs.md b/articles/ai-foundry/model-inference/how-to/use-structured-outputs.md
@@ -51,4 +51,4 @@ zone_pivot_groups: azure-ai-inference-samples
 * [Use embeddings models](use-embeddings.md)
 * [Use image embeddings models](use-image-embeddings.md)
 * [Use reasoning models](use-chat-reasoning.md)
-* [Azure AI Model Inference API](.././reference/reference-model-inference-api.md)
+* [Azure AI Foundry Models API](.././reference/reference-model-inference-api.md)
