Merge pull request #8781 from sdgilley/sdg-classic8

add classic banner to foundry-models, quickstarts, reference dirs

Author: prmerger-automator[bot]

articles/ai-foundry/foundry-models/concepts/content-filter.md

@@ -19,6 +19,8 @@ ai-usage: ai-assisted
 
 # Content filtering for Microsoft Foundry Models
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 
 > [!IMPORTANT]
 > The content filtering system doesn't apply to prompts and completions processed by audio models such as Whisper in Azure OpenAI in Microsoft Foundry Models. For more information, see [Audio models in Azure OpenAI](../../../ai-services/openai/concepts/models.md?tabs=standard-audio#standard-deployment-regional-models-by-endpoint).

articles/ai-foundry/foundry-models/concepts/default-safety-policies.md

@@ -17,6 +17,8 @@ ai-usage: ai-assisted
 
 # Default Guardrails and controls policies for Microsoft Foundry Models
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 Microsoft Foundry Models applies default safety to all models, excluding audio models such as Whisper in Azure OpenAI in Foundry Models. These configurations provide you with a responsible experience by default.
 
 Default safety aims to mitigate risks such as hate and fairness, sexual, violence, self-harm, protected material content, and user prompt injection attacks. To learn more about content filtering, read about [risk categories and severity levels](../../model-inference/concepts/content-filter.md).

articles/ai-foundry/foundry-models/how-to/configure-content-filters.md

@@ -20,6 +20,8 @@ ai-usage: ai-assisted
 
 # How to configure content filters for models in Microsoft Foundry
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 ::: zone pivot="ai-foundry-portal"
 [!INCLUDE [portal](../../foundry-models/includes/configure-content-filters/portal.md)]
 ::: zone-end

articles/ai-foundry/foundry-models/how-to/configure-deployment-policies.md

@@ -15,6 +15,8 @@ ai-usage: ai-assisted
 
 # Control model deployment with custom policies
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 When using models from Microsoft Foundry (formerly known Azure AI Services) and Azure OpenAI with [Foundry](https://ai.azure.com/?cid=learnDocs), you might need to use custom policies to control which [type of deployment](../../model-inference/concepts/deployment-types.md) options are available to users or which specific models users can deploy. This article guides you on how to create policies to control model deployments using Azure Policies. 
 
 > [!TIP]

articles/ai-foundry/foundry-models/how-to/configure-entra-id.md

@@ -20,6 +20,8 @@ ai-usage: ai-assisted
 
 # Configure key-less authentication with Microsoft Entra ID
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 ::: zone pivot="ai-foundry-portal"
 [!INCLUDE [portal](../../foundry-models/includes/configure-entra-id/portal.md)]
 ::: zone-end

articles/ai-foundry/foundry-models/how-to/configure-project-connection.md

@@ -17,6 +17,8 @@ reviewer: santiagxf
 
 # Configure a connection to use Microsoft Foundry Models in your AI project
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 ::: zone pivot="ai-foundry-portal"
 [!INCLUDE [portal](../../foundry-models/includes/configure-project-connection/portal.md)]
 ::: zone-end

articles/ai-foundry/foundry-models/how-to/create-model-deployments.md

@@ -20,6 +20,8 @@ ai.usage: ai-assisted
 
 # Add and configure models to Microsoft Foundry Models
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 ::: zone pivot="ai-foundry-portal"
 [!INCLUDE [portal](../../foundry-models/includes/create-model-deployments/portal.md)]
 ::: zone-end

articles/ai-foundry/foundry-models/how-to/quickstart-ai-project.md

@@ -16,6 +16,8 @@ reviewer: santiagxf
 
 # Configure your AI project to use Microsoft Foundry Models
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 If you already have an AI project in Microsoft Foundry, the model catalog deploys models from partner model providers as stand-alone endpoints in your project by default. Each model deployment has its own set of URI and credentials to access it. On the other hand, Azure OpenAI models are deployed to the Foundry resource or to the Azure OpenAI in Foundry Models resource.
 
 You can change this behavior and deploy both types of models to Foundry (formerly known Azure AI Services). Once configured, *deployments of models as serverless API deployments happen to the connected Foundry resource* instead to the project itself, giving you a single set of endpoint and credentials to access all the models deployed in Foundry. You can manage models from Azure OpenAI and partner model providers in the same way.

articles/ai-foundry/foundry-models/how-to/quickstart-create-resources.md

@@ -17,6 +17,8 @@ reviewer: santiagxf
 
 # Create and configure all the resources for Microsoft Foundry Models
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 ::: zone pivot="ai-foundry-portal"
 [!INCLUDE [portal](../../foundry-models/includes/create-resources/portal.md)]
 ::: zone-end

articles/ai-foundry/foundry-models/how-to/quickstart-github-models.md

@@ -15,6 +15,8 @@ recommendations: false
 
 # Upgrade from GitHub Models to Microsoft Foundry Models
 
+[!INCLUDE [classic-banner](../../includes/classic-banner.md)]
+
 In this article, you learn to develop a generative AI application by starting from GitHub Models and then upgrade your experience by deploying a Foundry Tools resource with Microsoft Foundry Models.
 
 [GitHub Models](https://docs.github.com/en/github-models/) are useful when you want to find and experiment with AI models for free as you develop a generative AI application. When you're ready to bring your application to production, upgrade your experience by deploying a Foundry Tools resource in an Azure subscription and start using Foundry Models. You don't need to change anything else in your code.