Merge branch 'MicrosoftDocs:main' into heidist-freshness

Author: HeidiSteen

articles/ai-services/agents/how-to/tools/bing-grounding.md

@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-agent-service
 ms.topic: how-to
-ms.date: 12/11/2024
+ms.date: 01/07/2025
 author: aahill
 ms.author: aahi
 zone_pivot_groups: selection-bing-grounding
@@ -35,13 +35,13 @@ Developers and end users don't have access to raw content returned from Groundin
 
 1. Create an Azure AI Agent by following the steps in the [quickstart](../../quickstart.md).
 
-1. Register the Bing Search provider.
+1. Manually [register](/azure/azure-resource-manager/management/resource-providers-and-types#register-resource-provider) Bing Search as an Azure resource provider. You must have permission to perform the `/register/action` operation for the resource provider. The permission is included in the **Contributor** and **Owner** roles.
 
    ```console
        az provider register --namespace 'Microsoft.Bing'
    ```
 
-1. Create a new Grounding with Bing Search resource in the [Azure portal](https://portal.azure.com/#create/Microsoft.BingGroundingSearch), and select the different fields in the creation form. Make sure you create this Grounding with Bing Search resource in the same resource group as your Azure AI Agent, AI Project, and other resources.
+1. Developers can create a new Grounding with Bing Search resource. Create a new Grounding with Bing Search resource in the [Azure portal](https://portal.azure.com/#create/Microsoft.BingGroundingSearch), and select the different fields in the creation form. Make sure you create this Grounding with Bing Search resource in the same resource group as your Azure AI Agent, AI Project, and other resources.
 
 1. After you have created a Grounding with Bing Search resource, you can find it in [Azure portal](https://portal.azure.com/#home). Navigate to the resource group you've created the resource in, search for the Grounding with Bing Search resource you have created.
 

articles/ai-services/agents/includes/bicep-setup.md

@@ -24,10 +24,18 @@ The following section shows you how to set up the required resources for getting
 
 **Standard Setup**: Agents use customer-owned, single-tenant search and storage resources. With this setup, you have full control and visibility over these resources, but you incur costs based on your usage.
 
+<!--
 | Description   | Resources  | Autodeploy |
 | -----------------------------------------------| -----------------------|----------------------|
 | Deploy a basic agent setup that uses Managed Identity authentication on the AI Services and storage account connections. | AI hub, AI project, AI Services | [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Fmaster%2Fquickstarts%2Fmicrosoft.azure-ai-agent-service%2Fbasic-agent-identity%2Fazuredeploy.json) |
 | Deploy a standard agent setup that uses Managed Identity authentication on the AI Services, storage account, and Azure AI Search connections. |AI hub, AI project, storage account, key vault, Azure AI Search, AI Services | [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Frefs%2Fheads%2Fmaster%2Fquickstarts%2Fmicrosoft.azure-ai-agent-service%2Fstandard-agent%2Fazuredeploy.json)|
+-->
+
+| Description and Autodeploy  |  Diagram (click to zoom in) |
+| -----------------------------------------------| -----------------------|
+| Deploy a basic agent setup that uses Managed Identity for authentication. Resources for the AI hub, AI project, storage account, and AI Services are created for you. <br><br> The AI Services account is connected to your project and hub, and a gpt-4o-mini model is deployed in the eastus region. A Microsoft-managed key vault is used by default. <br><br> [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Fmaster%2Fquickstarts%2Fmicrosoft.azure-ai-agent-service%2Fbasic-agent-identity%2Fazuredeploy.json) |  :::image type="content" source="../media/quickstart/basic-agent-setup-resources.png" alt-text="An architecture diagram for basic agent setup." lightbox="../media/quickstart/basic-agent-setup-resources.png"::: | 
+| Deploy a standard agent setup that uses Managed Identity for authentication. <br><br> Resources for the AI hub, AI project, key vault, storage account, AI Services, and AI Search are created for you. <br><br>The AI Services, AI Search, key vault, and storage account are connected to your project and hub. A gpt-4o-mini model is deployed in eastus region. <br><br> [![Deploy to Azure](https://aka.ms/deploytoazurebutton)](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure%2Fazure-quickstart-templates%2Frefs%2Fheads%2Fmaster%2Fquickstarts%2Fmicrosoft.azure-ai-agent-service%2Fstandard-agent%2Fazuredeploy.json) | :::image type="content" source="../media/quickstart/standard-agent-setup-resources.png" alt-text="An architecture diagram for standard agent setup." lightbox="../media/quickstart/standard-agent-setup-resources.png"::: |
+
 
 ### [Optional] Model selection in autodeploy template
 You can customize the model used by your agent by editing the model parameters in the autodeploy template. To deploy a different model, you need to update at least the `modelName` and `modelVersion` parameters. 
@@ -64,7 +72,7 @@ If you want to use an existing Azure OpenAI resource, you need to update the `ai
 
 For more information, see [how to use your own resources](../how-to/use-your-own-resources.md).
 
-
+<!--
 ## Basic agent setup resource architecture
 :::image type="content" source="../media/quickstart/basic-agent-setup-resources.png" alt-text="An architecture diagram for basic agent setup." lightbox="../media/quickstart/basic-agent-setup-resources.png":::
 
@@ -73,4 +81,5 @@ Resources for the AI hub, AI project, and AI Services are created for you. A sto
 ## Standard agent setup resource architecture
 :::image type="content" source="../media/quickstart/standard-agent-setup-resources.png" alt-text="An architecture diagram for standard agent setup." lightbox="../media/quickstart/standard-agent-setup-resources.png":::
 
-Resources for the AI hub, AI project, key vault, storage account, AI Services, and AI Search are created for you. The AI Services, AI Search, key vault, and storage account are connected to your project and hub. A gpt-4o-mini model is deployed in eastus region using the Azure OpenAI endpoint for your resource.
+Resources for the AI hub, AI project, key vault, storage account, AI Services, and AI Search are created for you. The AI Services, AI Search, key vault, and storage account are connected to your project and hub. A gpt-4o-mini model is deployed in eastus region using the Azure OpenAI endpoint for your resource.
+-->

articles/ai-services/agents/overview.md

@@ -65,7 +65,7 @@ What originally took hundreds of lines of code can now be done in just a few wit
 
 ### Comparing Azure agents and Azure OpenAI assistants
 
-Both services enable you to build agents using the same API and SDKs, but if you have additional enterprise requirements, you may want to consider using Azure AI Agent Service. Azure AI Agent Service provides all the capabilities of assistants in addition to:
+Both services enable you to build agents using the same API and SDKs, but if you have additional enterprise requirements, you might want to consider using Azure AI Agent Service. Azure AI Agent Service provides all the capabilities of assistants in addition to:
 
 **Flexible model selection** - Create agents that use Azure OpenAI models, or others such as Llama 3, Mistral and Cohere. Choose the most suitable model to meet your business needs.
 

articles/ai-services/agents/quotas-limits.md

@@ -21,7 +21,7 @@ The following sections provide you with a guide to the default quotas and limits
 
 | Limit Name | Limit Value |
 |--|--|
-| Max files per agent/thread | 10,000 when using the API or Azure AI Foundry portal. 20 when using Azure OpenAI Studio.|
+| Max files per agent/thread | 10,000 when using the API or Azure AI Foundry portal. In Azure OpenAI Studio the limit was 20.|
 | Max file size for agents & fine-tuning | 512 MB |
 | Max size for all uploaded files for agents |100 GB |  
 | agents token limit | 2,000,000 token limit |

articles/ai-services/anomaly-detector/concepts/best-practices-multivariate.md

@@ -185,7 +185,7 @@ to determine whether data at `2021-01-02T00:01:00Z` is anomalous. It moves on in
 
 Normally we recommend you to use  `severity` as the filter to sift out 'anomalies' that aren't so important to your business. Depending on your scenario and data pattern, those anomalies that are less important often have relatively lower `severity` values or standalone (discontinuous) high `severity` values like random spikes.
 
-In cases where you've found a need of more sophisticated rules than thresholds against `severity` or duration of continuous high `severity` values, you may want to use `score` to build more powerful filters. Understanding how MVAD is using `score` to determine anomalies may help:
+In cases where you've found a need of more sophisticated rules than thresholds against `severity` or duration of continuous high `severity` values, you might want to use `score` to build more powerful filters. Understanding how MVAD is using `score` to determine anomalies may help:
 
 We consider whether a data point is anomalous from both global and local perspective. If `score` at a timestamp is higher than a certain threshold, then the timestamp is marked as an anomaly. If `score` is lower than the threshold but is relatively higher in a segment, it's also marked as an anomaly.
 

articles/ai-services/computer-vision/how-to/background-removal.md

@@ -77,7 +77,7 @@ Authentication is done by adding the HTTP request header **Ocp-Apim-Subscription
 
 ## Select the image to analyze
 
-The code in this guide uses remote images referenced by URL. You may want to try different images on your own to see the full capability of the Image Analysis features.
+The code in this guide uses remote images referenced by URL. You might want to try different images on your own to see the full capability of the Image Analysis features.
 
 <!--
 #### [C#](#tab/csharp)

articles/ai-services/computer-vision/how-to/specify-recognition-model.md

@@ -126,7 +126,7 @@ If you'd like to compare the performances of different recognition models on you
 1. Train your **PersonGroup**s using the [Train Person Group] API.
 1. Test with [Identify From Person Group] on all four **PersonGroup**s and compare the results.
 
-If you normally specify a confidence threshold (a value between zero and one that determines how confident the model must be to identify a face), you may need to use different thresholds for different models. A threshold for one model isn't meant to be shared to another and won't necessarily produce the same results.
+If you normally specify a confidence threshold (a value between zero and one that determines how confident the model must be to identify a face), you might need to use different thresholds for different models. A threshold for one model isn't meant to be shared to another and won't necessarily produce the same results.
 
 ## Next steps
 

articles/ai-services/computer-vision/includes/environment-variables.md

@@ -30,7 +30,7 @@ setx VISION_KEY <your_key>
 setx VISION_ENDPOINT <your_endpoint>
 ```
 
-After you add the environment variables, you may need to restart any running programs that will read the environment variables, including the console window.
+After you add the environment variables, you might need to restart any running programs that will read the environment variables, including the console window.
 
 #### [Linux](#tab/linux)
 

articles/ai-services/computer-vision/includes/face-environment-variables.md

@@ -27,7 +27,7 @@ setx FACE_APIKEY <your_key>
 setx FACE_ENDPOINT <your_endpoint>
 ```
 
-After you add the environment variables, you may need to restart any running programs that will read the environment variables, including the console window.
+After you add the environment variables, you might need to restart any running programs that will read the environment variables, including the console window.
 
 #### [Linux](#tab/linux)
 

articles/ai-services/computer-vision/includes/how-to-guides/analyze-image-40-rest.md

@@ -28,7 +28,7 @@ Authentication is done by adding the HTTP request header **Ocp-Apim-Subscription
 
 ## Select the image to analyze
 
-The code in this guide uses remote images referenced by URL. You may want to try different images on your own to see the full capability of the Image Analysis features.
+The code in this guide uses remote images referenced by URL. You might want to try different images on your own to see the full capability of the Image Analysis features.
 
 ### Image URL
 When analyzing a remote image, you specify the image's URL by formatting the request body like this: `{"url":"https://learn.microsoft.com/azure/cognitive-services/computer-vision/images/windows-kitchen.jpg"}`. The **Content-Type** should be `application/json`.