fixes

Author: santiagxf

articles/ai-foundry/model-inference/includes/use-chat-reasoning/csharp.md

@@ -19,7 +19,7 @@ To complete this tutorial, you need:
 
 * A model with reasoning capabilities model deployment. If you don't have one read [Add and configure models to Azure AI services](../../how-to/create-model-deployments.md) to add a reasoning model. 
 
-  * This examples uses `DeepSeek-R1`.
+  * This example uses `DeepSeek-R1`.
 
 * Install the Azure AI inference package with the following command:
 
@@ -46,7 +46,7 @@ ChatCompletionsClient client = new ChatCompletionsClient(
 ```
 
 > [!TIP]
-> Verify that you have deployed the model to Azure AI Services resource with the Azure AI model inference API. `Deepseek-R1` is also available as Serverless API Endpoints. However, those endpoints doesn't take the parameter `model` as explained in this tutorial. You can verify that by going to [Azure AI Foundry portal]() > Models + endpoints, and verify that the model is listed under the section **Azure AI Services**.
+> Verify that you have deployed the model to Azure AI Services resource with the Azure AI model inference API. `Deepseek-R1` is also available as Serverless API Endpoints. However, those endpoints don't take the parameter `model` as explained in this tutorial. You can verify that by going to [Azure AI Foundry portal]() > Models + endpoints, and verify that the model is listed under the section **Azure AI Services**.
 
 If you have configured the resource to with **Microsoft Entra ID** support, you can use the following code snippet to create a client.
 
@@ -60,7 +60,7 @@ client = new ChatCompletionsClient(
 
 ### Create a chat completion request
 
-The following example shows how you can create a basic reasoning capabilities with chat request to the model.
+The following example shows how you can create a basic chat request to the model.
 
 ```csharp
 ChatCompletionsOptions requestOptions = new ChatCompletionsOptions()

articles/ai-foundry/model-inference/includes/use-chat-reasoning/java.md

@@ -19,7 +19,7 @@ To complete this tutorial, you need:
 
 * A model with reasoning capabilities model deployment. If you don't have one read [Add and configure models to Azure AI services](../../how-to/create-model-deployments.md) to add a reasoning model. 
 
-  * This examples uses `DeepSeek-R1`.
+  * This examples use `DeepSeek-R1`.
 
 * Add the [Azure AI inference package](https://aka.ms/azsdk/azure-ai-inference/java/reference) to your project:
 
@@ -69,7 +69,7 @@ ChatCompletionsClient client = new ChatCompletionsClient(
 ```
 
 > [!TIP]
-> Verify that you have deployed the model to Azure AI Services resource with the Azure AI model inference API. `Deepseek-R1` is also available as Serverless API Endpoints. However, those endpoints doesn't take the parameter `model` as explained in this tutorial. You can verify that by going to [Azure AI Foundry portal]() > Models + endpoints, and verify that the model is listed under the section **Azure AI Services**.
+> Verify that you have deployed the model to Azure AI Services resource with the Azure AI model inference API. `Deepseek-R1` is also available as Serverless API Endpoints. However, those endpoints don't take the parameter `model` as explained in this tutorial. You can verify that by going to [Azure AI Foundry portal]() > Models + endpoints, and verify that the model is listed under the section **Azure AI Services**.
 
 If you have configured the resource to with **Microsoft Entra ID** support, you can use the following code snippet to create a client.
 
@@ -83,7 +83,7 @@ client = new ChatCompletionsClient(
 
 ### Create a chat completion request
 
-The following example shows how you can create a basic reasoning capabilities with chat request to the model.
+The following example shows how you can create a basic chat request to the model.
 
 ```java
 ChatCompletionsOptions requestOptions = new ChatCompletionsOptions()

articles/ai-foundry/model-inference/includes/use-chat-reasoning/javascript.md

@@ -19,7 +19,7 @@ To complete this tutorial, you need:
 
 * A model with reasoning capabilities model deployment. If you don't have one read [Add and configure models to Azure AI services](../../how-to/create-model-deployments.md) to add a reasoning model. 
 
-  * This examples uses `DeepSeek-R1`.
+  * This examples use `DeepSeek-R1`.
 
 * Install the [Azure Inference library for JavaScript](https://aka.ms/azsdk/azure-ai-inference/javascript/reference) with the following command:
 
@@ -43,6 +43,9 @@ const client = new ModelClient(
 );
 ```
 
+> [!TIP]
+> Verify that you have deployed the model to Azure AI Services resource with the Azure AI model inference API. `Deepseek-R1` is also available as Serverless API Endpoints. However, those endpoints don't take the parameter `model` as explained in this tutorial. You can verify that by going to [Azure AI Foundry portal]() > Models + endpoints, and verify that the model is listed under the section **Azure AI Services**.
+
 If you have configured the resource to with **Microsoft Entra ID** support, you can use the following code snippet to create a client.
 
 ```javascript
@@ -62,7 +65,7 @@ const client = new ModelClient(
 
 ### Create a chat completion request
 
-The following example shows how you can create a basic reasoning capabilities with chat request to the model.
+The following example shows how you can create a basic chat request to the model.
 
 ```javascript
 var messages = [

articles/ai-foundry/model-inference/includes/use-chat-reasoning/python.md

@@ -19,7 +19,7 @@ To complete this tutorial, you need:
 
 * A model with reasoning capabilities model deployment. If you don't have one read [Add and configure models to Azure AI services](../../how-to/create-model-deployments.md) to add a reasoning model. 
 
-  * This examples uses `DeepSeek-R1`.
+  * This examples use `DeepSeek-R1`.
 
 * Install the [Azure AI inference package](https://aka.ms/azsdk/azure-ai-inference/python/reference) with the following command:
 
@@ -44,7 +44,7 @@ client = ChatCompletionsClient(
 ```
 
 > [!TIP]
-> Verify that you have deployed the model to Azure AI Services resource with the Azure AI model inference API. `Deepseek-R1` is also available as Serverless API Endpoints. However, those endpoints doesn't take the parameter `model` as explained in this tutorial. You can verify that by going to [Azure AI Foundry portal]() > Models + endpoints, and verify that the model is listed under the section **Azure AI Services**.
+> Verify that you have deployed the model to Azure AI Services resource with the Azure AI model inference API. `Deepseek-R1` is also available as Serverless API Endpoints. However, those endpoints don't take the parameter `model` as explained in this tutorial. You can verify that by going to [Azure AI Foundry portal]() > Models + endpoints, and verify that the model is listed under the section **Azure AI Services**.
 
 If you have configured the resource to with **Microsoft Entra ID** support, you can use the following code snippet to create a client.
 
@@ -63,7 +63,7 @@ client = ChatCompletionsClient(
 
 ### Create a chat completion request
 
-The following example shows how you can create a basic reasoning capabilities with chat request to the model.
+The following example shows how you can create a basic chat request to the model.
 
 ```python
 from azure.ai.inference.models import SystemMessage, UserMessage

articles/ai-foundry/model-inference/includes/use-chat-reasoning/rest.md

@@ -19,7 +19,7 @@ To complete this tutorial, you need:
 
 * A model with reasoning capabilities model deployment. If you don't have one read [Add and configure models to Azure AI services](../../how-to/create-model-deployments.md) to add a reasoning model. 
 
-  * This examples uses `DeepSeek-R1`.
+  * This examples use `DeepSeek-R1`.
 
 ## Use reasoning capabilities with chat
 
@@ -31,6 +31,9 @@ Content-Type: application/json
 api-key: <key>
 ```
 
+> [!TIP]
+> Verify that you have deployed the model to Azure AI Services resource with the Azure AI model inference API. `Deepseek-R1` is also available as Serverless API Endpoints. However, those endpoints don't take the parameter `model` as explained in this tutorial. You can verify that by going to [Azure AI Foundry portal]() > Models + endpoints, and verify that the model is listed under the section **Azure AI Services**.
+
 If you have configured the resource with **Microsoft Entra ID** support, pass you token in the `Authorization` header:
 
 ```http
@@ -41,7 +44,7 @@ Authorization: Bearer <token>
 
 ### Create a chat completion request
 
-The following example shows how you can create a basic reasoning capabilities with chat request to the model.
+The following example shows how you can create a basic chat request to the model.
 
 ```json
 {