fixing merge conflict

Author: aahill

articles/ai-foundry/model-inference/breadcrumb/toc.yml

@@ -2,10 +2,10 @@
   tocHref: /azure/
   topicHref: /azure/index
   items:
-  - name: Azure AI services
-    tocHref: /azure/ai-services/
-    topicHref: /azure/ai-services/index
+  - name: AI Foundry
+    tocHref: /azure/ai-foundry/
+    topicHref: /azure/ai-studio/index
     items:
-    - name: Azure AI Model Inference
-      tocHref: /azure/ai-foundry/
+    - name: Model Inference
+      tocHref: /azure/ai-foundry/model-inference/
       topicHref: /azure/ai-foundry/model-inference/index

articles/ai-foundry/model-inference/concepts/models.md

@@ -17,6 +17,9 @@ ms.custom: references_regions, tool_generated
 
 Azure AI model inference in Azure AI Foundry gives you access to flagship models in Azure AI to consume them as APIs without hosting them on your infrastructure.
 
+> [!TIP]
+> DeepSeek-R1 is available for deployment as [Serverless API endpoint](../../../ai-studio/how-to/deploy-models-deepseek.md).
+
 :::image type="content" source="../media/models/models-catalog.gif" alt-text="An animation showing Azure AI studio model catalog section and the models available." lightbox="../media/models/models-catalog.gif":::
 
 Model availability varies by model provider, deployment SKU, and cloud. All models available in Azure AI Model Inference support the [Global standard](deployment-types.md#global-standard) deployment type which uses global capacity to guarantee throughput. [Azure OpenAI models](#azure-openai) also support regional deployments and [sovereign clouds](/entra/identity-platform/authentication-national-cloud)—Azure Government, Azure Germany, and Azure China 21Vianet.

articles/ai-foundry/model-inference/how-to/quickstart-ai-project.md

@@ -141,7 +141,7 @@ Use the parameter `model="<deployment-name>` to route your request to this deplo
 
 ## Move from Serverless API Endpoints to Azure AI model inference
 
-Although you configured the project to use the Azure AI model inference, existing model deployments continue to exit 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 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:
 
 1. Recreate the model deployment in Azure AI model inference. This model deployment is accessible under the **Azure AI model inference endpoint**.
 

articles/ai-foundry/model-inference/overview.md

@@ -18,6 +18,9 @@ recommendations: false
 
 Azure AI model inference provides access to the most powerful models available in the Azure AI model catalog. The models come from key model providers in the industry, including OpenAI, Microsoft, Meta, Mistral, Cohere, G42, and AI21 Labs. These models can be integrated with software solutions to deliver a wide range of tasks that include content generation, summarization, image understanding, semantic search, and code generation.
 
+> [!TIP]
+> DeepSeek-R1 is available for deployment as [Serverless API endpoint](../../ai-studio/how-to/deploy-models-deepseek.md).
+
 Azure AI model inference provides a way to **consume models as APIs without hosting them on your infrastructure**. Models are hosted in a Microsoft-managed infrastructure, which enables API-based access to the model provider's model. API-based access can dramatically reduce the cost of accessing a model and simplify the provisioning experience.
 
 Azure AI model inference is part of Azure AI Services, and users can access the service through [REST APIs](./reference/reference-model-inference-api.md), [SDKs in several languages](supported-languages.md) such as Python, C#, JavaScript, and Java. You can also use the Azure AI model inference from [Azure AI Foundry by configuring a connection](how-to/configure-project-connection.md).

articles/ai-foundry/model-inference/reference/reference-model-inference-api.md

@@ -49,7 +49,8 @@ Models deployed to [serverless API endpoints](../../../ai-studio/how-to/deploy-m
 > * [Mistral-Large](../../../ai-studio/how-to/deploy-models-mistral.md)
 > * [Jais](../../../ai-studio/how-to/deploy-jais-models.md) family of models
 > * [Jamba](../../../ai-studio/how-to/deploy-models-jamba.md) family of models
-> * [Phi-3](../../../ai-studio/how-to/deploy-models-phi-3.md) family of models
+> * [Phi-3](../../../ai-studio/how-to/deploy-models-phi-3.md) and [Phi-4](../../../ai-studio/how-to/deploy-models-phi-4.md) family of models
+> * [DeepSeek-R1](../../../ai-studio/how-to/deploy-models-deepseek.md) family of models.
 
 Models deployed to [managed inference](../../../ai-studio/concepts/deployments-overview.md):
 

articles/ai-services/agents/concepts/model-region-support.md

@@ -7,7 +7,7 @@ author: aahill
 ms.author: aahi
 ms.service: azure-ai-agent-service
 ms.topic: conceptual
-ms.date: 01/27/2025
+ms.date: 01/29/2025
 ms.custom: azure-ai-agents
 ---
 
@@ -27,6 +27,7 @@ Azure AI Agent Service supports the same models as the chat completions API in A
 | francecentral | -                          | -                          | -                               | ✅                  | ✅                           | -                           | -                               | ✅ | ✅                         | ✅                          | -                          | ✅                             |
 | japaneast     | -                          | -                          | -                               | -                   | -                           | -                           | -                               | -                      | ✅                         | -                          | ✅                         | ✅                              |
 | norwayeast    |-  |  - |  - | -  | ✅ | -  |-  | -  | -  | -  | -  | - |
+| southindia    | - | - | - | - | ✅ | - | - | - | - | ✅ | ✅ | - |
 | swedencentral    | ✅ | ✅ | ✅ | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | - | ✅ |
 | uksouth       | -                          | -                          | -                               | -                   | ✅                          | ✅                           | -                               | -                       | ✅                          | ✅                         | ✅                          | ✅                             |
 | westus        | ✅                         | ✅                          | ✅                            | -                   | ✅                          | -                           | ✅                               | - | -                          | ✅                         | ✅                          | -                              |
@@ -37,9 +38,10 @@ Azure AI Agent Service supports the same models as the chat completions API in A
 
 The Azure AI Agent Service also supports the following models from the Azure AI Foundry model catalog.
 
-* Llama 3.1-70B-instruct
+* Meta-Llama-405B-Instruct
 * Mistral-large-2407
-* Cohere command R+
+* Cohere-command-r-plus
+* Cohere-command-r
 
 To use these models, you can use Azure AI Foundry portal to make a deployment, and then reference the deployment name in your agent. For example:
 

articles/ai-services/agents/how-to/tools/azure-functions.md

@@ -6,7 +6,7 @@ services: azure-ai-agent-service
 manager: nitinme
 ms.service: azure-ai-agent-service
 ms.topic: how-to
-ms.date: 12/11/2024
+ms.date: 01/30/2025
 author: aahill
 ms.author: aahi
 ms.custom: azure-ai-agents

articles/ai-services/agents/how-to/tools/function-calling.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: 01/30/2025
 author: aahill
 ms.author: aahi
 zone_pivot_groups: selection-function-calling
@@ -22,12 +22,6 @@ Azure AI Agents supports function calling, which allows you to describe the stru
 > [!NOTE]
 > Runs expire ten minutes after creation. Be sure to submit your tool outputs before the expiration.
 
-### Supported models
-
-The [models page](../../concepts/model-region-support.md) contains the most up-to-date information on regions/models where Agents are supported.
-
-To use all features of function calling including parallel functions, you need to use a model that was released after November 6, 2023.
-
 ### Usage support
 
 |Azure AI foundry support  | Python SDK |	C# SDK | Basic agent setup | Standard agent setup |

articles/ai-services/agents/includes/quickstart-csharp.md

@@ -16,8 +16,6 @@ ms.date: 01/15/2025
 * Make sure you have the **Azure AI Developer** [RBAC role](../../../ai-studio/concepts/rbac-ai-studio.md) assigned at the appropriate level.
 * Install [the Azure CLI and the machine learning extension](/azure/machine-learning/how-to-configure-cli). If you have the CLI already installed, make sure it's updated to the latest version.
 
-[!INCLUDE [rbac-roles](rbac-roles.md)]
-
 [!INCLUDE [bicep-setup](bicep-setup.md)]
 
 ## Configure and run an agent

articles/ai-services/agents/includes/quickstart-python-openai.md

@@ -18,8 +18,6 @@ ms.date: 11/13/2024
 * You need the **Cognitive Services OpenAI User** role assigned to use the Azure AI Services resource.
 * Install [the Azure CLI and the machine learning extension](/azure/machine-learning/how-to-configure-cli). If you have the CLI already installed, make sure it's updated to the latest version.
 
-[!INCLUDE [rbac-roles](rbac-roles.md)]
-
 [!INCLUDE [bicep-setup](bicep-setup.md)]
 
 ## Configure and run an agent