update branding

Instructions/Exercises/01-get-started-azure-openai.md

@@ -5,7 +5,7 @@ lab:
 
 # Get started with Azure OpenAI service
 
-Azure OpenAI Service brings the generative AI models developed by OpenAI to the Azure platform, enabling you to develop powerful AI solutions that benefit from the security, scalability, and integration of services provided by the Azure cloud platform. In this exercise, you'll learn how to get started with Azure OpenAI by provisioning the service as an Azure resource and using Azure AI Studio to deploy and explore generative AI models.
+Azure OpenAI Service brings the generative AI models developed by OpenAI to the Azure platform, enabling you to develop powerful AI solutions that benefit from the security, scalability, and integration of services provided by the Azure cloud platform. In this exercise, you'll learn how to get started with Azure OpenAI by provisioning the service as an Azure resource and using Azure AI Foundry to deploy and explore generative AI models.
 
 In the scenario for this exercise, you will perform the role of a software developer who has been tasked to implement an AI agent that can use generative AI to help a marketing organization improve its effectiveness at reaching customers and advertising new products. The techniques used in the exercise can be applied to any scenario where an organization wants to use generative AI models to help employees be more effective and productive.
 
@@ -39,12 +39,12 @@ If you don't already have one, provision an Azure OpenAI resource in your Azure
 
 ## Deploy a model
 
-Azure provides a web-based portal named **Azure AI Studio**, that you can use to deploy, manage, and explore models. You'll start your exploration of Azure OpenAI by using Azure AI Studio to deploy a model.
+Azure provides a web-based portal named **Azure AI Foundry portal**, that you can use to deploy, manage, and explore models. You'll start your exploration of Azure OpenAI by using Azure AI Foundry portal to deploy a model.
 
-> **Note**: As you use Azure AI Studio, message boxes suggesting tasks for you to perform may be displayed. You can close these and follow the steps in this exercise.
+> **Note**: As you use Azure AI Foundry portal, message boxes suggesting tasks for you to perform may be displayed. You can close these and follow the steps in this exercise.
 
-1. In the Azure portal, on the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Studio**.
-1. In Azure AI Studio, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one, create a new deployment of the **gpt-35-turbo-16k** model with the following settings:
+1. In the Azure portal, on the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Foundry portal** (previously AI Studio).
+1. In Azure AI Foundry portal, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one, create a new deployment of the **gpt-35-turbo-16k** model with the following settings:
     - **Deployment name**: *A unique name of your choice*
     - **Model**: gpt-35-turbo-16k *(if the 16k model isn't available, choose gpt-35-turbo)*
     - **Model version**: *Use default version*
@@ -57,7 +57,7 @@ Azure provides a web-based portal named **Azure AI Studio**, that you can use to
 
 ## Use the Chat playground
 
-Now that you've deployed a model, you can use it to generate responses based on natural language prompts. The *Chat* playground in Azure AI Studio provides a chatbot interface for GPT 3.5 and higher models.
+Now that you've deployed a model, you can use it to generate responses based on natural language prompts. The *Chat* playground in Azure AI Foundry portal provides a chatbot interface for GPT 3.5 and higher models.
 
 > **Note:** The *Chat* playground uses the *ChatCompletions* API rather than the older *Completions* API that is used by the *Completions* playground. The Completions playground is provided for compatibility with older models.
 
@@ -135,9 +135,9 @@ You've explored how the system message, examples, and prompts can help refine th
 
 ## Deploy your model to a web app
 
-Now that you've explored some of the capabilities of a generative AI model in the Azure AI Studio playground, you can deploy an Azure web app to provide a basic AI agent interface through which users can chat with the model.
+Now that you've explored some of the capabilities of a generative AI model in the Azure AI Foundry playground, you can deploy an Azure web app to provide a basic AI agent interface through which users can chat with the model.
 
-> **Note**: Azure AI Studio is still in preview. For some users, deploying to the web app cannot be deployed due to a bug in the template in the studio. If that's the case, skip this section.
+> **Note**: For some users, deploying to the web app cannot be deployed due to a bug in the template in the studio. If that's the case, skip this section.
 
 1. At the top right of the **Chat** playground page, in the **Deploy to** menu, select **A new web app**.
 1. In the **Deploy to a web app** dialog box, create a new web app with the following settings:
@@ -160,7 +160,7 @@ Now that you've explored some of the capabilities of a generative AI model in th
 
     > **Note**: You deployed the *model* to a web app, but this deployment doesn't include the system settings and parameters you set in the playground; so the response may not reflect the examples you specified in the playground. In a real scenario, you would add logic to your application to modify the prompt so that it includes the appropriate contextual data for the kinds of response you want to generate. This kind of customization is beyond the scope of this introductory-level exercise, but you can learn about prompt engineering techniques and Azure OpenAI APIs in other exercises and product documentation.
 
-1. When you have finished experimenting with your model in the web app, close the web app tab in your browser to return to Azure AI Studio.
+1. When you have finished experimenting with your model in the web app, close the web app tab in your browser to return to Azure AI Foundry portal.
 
 ## Clean up
 

Instructions/Exercises/02-natural-language-azure-openai.md

@@ -39,12 +39,12 @@ If you don't already have one, provision an Azure OpenAI resource in your Azure
 
 ## Deploy a model
 
-Azure provides a web-based portal named **Azure AI Studio**, that you can use to deploy, manage, and explore models. You'll start your exploration of Azure OpenAI by using Azure AI Studio to deploy a model.
+Azure provides a web-based portal named **Azure AI Foundry portal**, that you can use to deploy, manage, and explore models. You'll start your exploration of Azure OpenAI by using Azure AI Foundry portal to deploy a model.
 
-> **Note**: As you use Azure AI Studio, message boxes suggesting tasks for you to perform may be displayed. You can close these and follow the steps in this exercise.
+> **Note**: As you use Azure AI Foundry portal, message boxes suggesting tasks for you to perform may be displayed. You can close these and follow the steps in this exercise.
 
-1. In the Azure portal, on the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Studio**.
-1. In Azure AI Studio, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one, create a new deployment of the **gpt-35-turbo-16k** model with the following settings:
+1. In the Azure portal, on the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Foundry portal** (previously AI Studio).
+1. In Azure AI Foundry portal, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one, create a new deployment of the **gpt-35-turbo-16k** model with the following settings:
     - **Deployment name**: *A unique name of your choice*
     - **Model**: gpt-35-turbo-16k *(if the 16k model isn't available, choose gpt-35-turbo)*
     - **Model version**: *Use default version*
@@ -97,7 +97,7 @@ Applications for both C# and Python have been provided. Both apps feature the sa
     
 4. Update the configuration values to include:
     - The  **endpoint** and a **key** from the Azure OpenAI resource you created (available on the **Keys and Endpoint** page for your Azure OpenAI resource in the Azure portal)
-    - The **deployment name** you specified for your model deployment (available in the **Deployments** page in Azure AI studio).
+    - The **deployment name** you specified for your model deployment (available in the **Deployments** page in Azure AI Foundry portal).
 5. Save the configuration file.
 
 ## Add code to use the Azure OpenAI service

Instructions/Exercises/03-prompt-engineering.md

@@ -39,12 +39,12 @@ If you don't already have one, provision an Azure OpenAI resource in your Azure
 
 ## Deploy a model
 
-Azure provides a web-based portal named **Azure AI Studio**, that you can use to deploy, manage, and explore models. You'll start your exploration of Azure OpenAI by using Azure AI Studio to deploy a model.
+Azure provides a web-based portal named **Azure AI Foundry portal**, that you can use to deploy, manage, and explore models. You'll start your exploration of Azure OpenAI by using Azure AI Foundry portal to deploy a model.
 
-> **Note**: As you use Azure AI Studio, message boxes suggesting tasks for you to perform may be displayed. You can close these and follow the steps in this exercise.
+> **Note**: As you use Azure AI Foundry portal, message boxes suggesting tasks for you to perform may be displayed. You can close these and follow the steps in this exercise.
 
-1. In the Azure portal, on the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Studio**.
-1. In Azure AI Studio, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one, create a new deployment of the **gpt-35-turbo-16k** model with the following settings:
+1. In the Azure portal, on the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Foundry portal** (previously AI Studio).
+1. In Azure AI Foundry portal, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one, create a new deployment of the **gpt-35-turbo-16k** model with the following settings:
     - **Deployment name**: *A unique name of your choice*
     - **Model**: gpt-35-turbo-16k *(if the 16k model isn't available, choose gpt-35-turbo)*
     - **Model version**: *Use default version*
@@ -210,7 +210,7 @@ Applications for both C# and Python have been provided, and both apps feature th
     
 4. Update the configuration values to include:
     - The  **endpoint** and a **key** from the Azure OpenAI resource you created (available on the **Keys and Endpoint** page for your Azure OpenAI resource in the Azure portal)
-    - The **deployment name** you specified for your model deployment (available in the **Deployments** page in Azure AI Studio).
+    - The **deployment name** you specified for your model deployment (available in the **Deployments** page in Azure AI Foundry portal).
 5. Save the configuration file.
 
 ## Add code to use the Azure OpenAI service

Instructions/Exercises/04-code-generation.md

@@ -39,12 +39,12 @@ If you don't already have one, provision an Azure OpenAI resource in your Azure
 
 ## Deploy a model
 
-Azure provides a web-based portal named **Azure AI Studio**, that you can use to deploy, manage, and explore models. You'll start your exploration of Azure OpenAI by using Azure AI Studio to deploy a model.
+Azure provides a web-based portal named **Azure AI Foundry portal**, that you can use to deploy, manage, and explore models. You'll start your exploration of Azure OpenAI by using Azure AI Foundry portal to deploy a model.
 
-> **Note**: As you use Azure AI Studio, message boxes suggesting tasks for you to perform may be displayed. You can close these and follow the steps in this exercise.
+> **Note**: As you use Azure AI Foundry portal, message boxes suggesting tasks for you to perform may be displayed. You can close these and follow the steps in this exercise.
 
-1. In the Azure portal, on the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Studio**.
-1. In Azure AI Studio, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one, create a new deployment of the **gpt-35-turbo-16k** model with the following settings:
+1. In the Azure portal, on the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Foundry portal** (previously AI Studio).
+1. In Azure AI Foundry portal, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one, create a new deployment of the **gpt-35-turbo-16k** model with the following settings:
     - **Deployment name**: *A unique name of your choice*
     - **Model**: gpt-35-turbo-16k *(if the 16k model isn't available, choose gpt-35-turbo)*
     - **Model version**: *Use default version*
@@ -154,7 +154,7 @@ Applications for both C# and Python have been provided, as well as a sample text
     
 4. Update the configuration values to include:
     - The  **endpoint** and a **key** from the Azure OpenAI resource you created (available on the **Keys and Endpoint** page for your Azure OpenAI resource in the Azure portal)
-    - The **deployment name** you specified for your model deployment (available in the **Deployments** page in Azure AI Studio).
+    - The **deployment name** you specified for your model deployment (available in the **Deployments** page in Azure AI Foundry portal).
 5. Save the configuration file.
 
 ## Add code to use your Azure OpenAI service model

Instructions/Exercises/05-generate-images.md

@@ -26,8 +26,8 @@ Before you can use Azure OpenAI to generate images, you must provision an Azure
     > \* DALL-E 3 models are only available in Azure OpenAI service resources in the **East US** and **Sweden Central** regions.
 
 1. Wait for deployment to complete. Then go to the deployed Azure OpenAI resource in the Azure portal.
-1. On the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Studio**.
-1. In Azure AI Studio, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one for DALL-E 3, create a new deployment of the **dall-e-3** model with the following settings:
+1. On the **Overview** page for your Azure OpenAI resource, scroll down to the **Get Started** section and select the button to go to **AI Foundry portal** (previously AI Studio).
+1. In Azure AI Foundry portal, in the pane on the left, select the **Deployments** page and view your existing model deployments. If you don't already have one for DALL-E 3, create a new deployment of the **dall-e-3** model with the following settings:
     - **Deployment name**: dalle3
     - **Model version**: *Use default version*
     - **Deployment type**: Standard
@@ -38,16 +38,16 @@ Before you can use Azure OpenAI to generate images, you must provision an Azure
 
 ## Explore image-generation in the images playground
 
-You can use the Images playground in **Azure AI Studio** to experiment with image generation.
+You can use the Images playground in **Azure AI Foundry portal** to experiment with image generation.
 
-1. In the **Images playground** section, your deployment of DALL-E 3 should be automatically selected. If not, select it from the deployment dropdown.
+1. In the **Images** playground section, your deployment of DALL-E 3 should be automatically selected. If not, select it from the deployment dropdown.
 1. In the **Prompt** box, enter a description of an image you'd like to generate. For example, `An elephant on a skateboard` Then select **Generate** and view the image that is generated.
 
-    ![The Images Playground in Azure AI Studio with a generated image.](../media/images-playground.png)
+    ![The Images Playground in Azure AI Foundry portal with a generated image.](../media/images-playground.png)
 
 1. Modify the prompt to provide a more specific description. For example `An elephant on a skateboard in the style of Picasso`. Then generate the new image and review the results.
 
-    ![The Images Playground in Azure AI Studio with two generated images.](../media/images-playground-new-style.png)
+    ![The Images Playground in Azure AI Foundry portal with two generated images.](../media/images-playground-new-style.png)
 
 ## Use the REST API to generate images
 

Instructions/Exercises/06-use-own-data.md

@@ -73,10 +73,10 @@ You're going to use two AI models in this exercise:
 - A text embedding model to *vectorize* the text in the brochures so it can be indexed efficiently for use in grounding prompts.
 - A GPT model that you application can use to generate responses to prompts that are grounded in your data.
 
-To deploy these models, you'll use AI Studio.
+To deploy these models, you'll use AI Foundry.
 
-1. In the Azure portal, navigate to your Azure OpenAI resource. Then use the link to open your resource in **Azure AI Studio**..
-1. In Azure AI Studio, on the **Deployments** page, view your existing model deployments. Then create a new base model deployment of the **text-embedding-ada-002** model with the following settings:
+1. In the Azure portal, navigate to your Azure OpenAI resource. Then use the link to open your resource in **Azure AI Foundry portal**..
+1. In Azure AI Foundry portal, on the **Deployments** page, view your existing model deployments. Then create a new base model deployment of the **text-embedding-ada-002** model with the following settings:
     - **Deployment name**: text-embedding-ada-002
     - **Model**: text-embedding-ada-002
     - **Model version**: *The default version*
@@ -161,7 +161,7 @@ Applications for both C# and Python have been provided, and both apps feature th
     
 4. Update the configuration values to include:
     - The  **endpoint** and a **key** from the Azure OpenAI resource you created (available on the **Keys and Endpoint** page for your Azure OpenAI resource in the Azure portal)
-    - The **deployment name** you specified for your gpt-35-turbo model deployment (available in the **Deployments** page in Azure AI Studio).
+    - The **deployment name** you specified for your gpt-35-turbo model deployment (available in the **Deployments** page in Azure AI Foundry portal).
     - The endpoint for your search service (the **Url** value on the overview page for your search resource in the Azure portal).
     - A **key** for your search resource (available in the **Keys** page for your search resource in the Azure portal - you can use either of the admin keys)
     - The name of the search index (which should be `margies-index`).