fixing links

Author: Blackmist

articles/ai-foundry/ai-services/content-safety-overview.md

@@ -46,4 +46,4 @@ Refer to the [Content Safety overview](/azure/ai-services/content-safety/overvie
 
 ## Next step
 
-Get started using Azure AI Content Safety in [Azure AI Foundry portal](https://ai.azure.com) by following the [How-to guide](./how-to/content-safety.md).
+Get started using Azure AI Content Safety in [Azure AI Foundry portal](https://ai.azure.com) by following the [How-to guide](/azure/ai-services/content-safety/how-to/foundry).

articles/ai-foundry/ai-services/how-to/connect-azure-openai.md

@@ -100,7 +100,7 @@ Here are a few guides to help you get started with Azure OpenAI Service playgrou
 - [Quickstart: Use the chat playground](../../quickstarts/get-started-playground.md)
 - [Quickstart: Get started using Azure OpenAI Assistants](../../../ai-services/openai/assistants-quickstart.md?context=/azure/ai-studio/context/context)
 - [Quickstart: Use GPT-4o in the real-time audio playground](../../../ai-services/openai/realtime-audio-quickstart.md?context=/azure/ai-studio/context/context)
-- [Quickstart: Analyze images and video in the chat playground](../../quickstarts/multimodal-vision.md)
+- [Quickstart: Analyze images and video in the chat playground](/azure/ai-services/openai/gpt-v-quickstart)
 
 Each playground has different model requirements and capabilities. The supported regions vary depending on the model. For more information about model availability per region, see the [Azure OpenAI Service models documentation](../../../ai-services/openai/concepts/models.md).
 
@@ -145,5 +145,5 @@ At some point, you want to develop apps with code. Here are some developer resou
 
 ## Related content
 
-- [Azure OpenAI in Azure AI Foundry portal](../../azure-openai-in-ai-studio.md)
+- [Azure OpenAI in Azure AI Foundry portal](../../azure-openai-in-ai-foundry.md)
 - [Use Azure AI services resources](./connect-ai-services.md)

articles/ai-foundry/concepts/ai-resources.md

@@ -128,6 +128,6 @@ In the Azure portal, you can find resources that correspond to your project in A
 
 ## Next steps
 
-- [Quickstart: Analyze images and video in the chat playground](../quickstarts/multimodal-vision.md)
-- [Learn more about Azure AI Foundry](../what-is-ai-studio.md)
+- [Quickstart: Analyze images and video in the chat playground](/azure/ai-services/openai/gpt-v-quickstart)
+- [Learn more about Azure AI Foundry](../what-is-ai-foundry.md)
 - [Learn more about projects](../how-to/create-projects.md)

articles/ai-foundry/concepts/architecture.md

@@ -28,7 +28,7 @@ At the top level, Azure AI Foundry provides access to the following resources:
 
     When you use Azure AI Foundry portal, you can directly work with Azure OpenAI without an Azure Studio project. Or you can use Azure OpenAI through a project.
 
-    For more information, visit [Azure OpenAI in Azure AI Foundry portal](../azure-openai-in-ai-studio.md).
+    For more information, visit [Azure OpenAI in Azure AI Foundry portal](../azure-openai-in-ai-foundry.md).
 
 - **Management center**: The management center streamlines governance and management of Azure AI Foundry resources such as hubs, projects, connected resources, and deployments.
 
@@ -108,7 +108,7 @@ Azure AI services including Azure OpenAI provide control plane endpoints for ope
 
 To reduce the complexity of Azure RBAC management, Azure AI Foundry provides a *control plane proxy* that allows you to perform operations on connected Azure AI services and Azure OpenAI resources. Performing operations on these resources through the control plane proxy only requires Azure RBAC permissions on the hub. The Azure AI Foundry service then performs the call to the Azure AI services or Azure OpenAI control plane endpoint on your behalf.
 
-For more information, see [Role-based access control in Azure AI Foundry portal](rbac-ai-studio.md).
+For more information, see [Role-based access control in Azure AI Foundry portal](rbac-ai-foundry.md).
 
 ## Attribute-based access control
 

articles/ai-foundry/faq.yml

@@ -82,5 +82,5 @@ sections:
 additionalContent: |
 
   ## Next steps
-  - [Azure AI Foundry](what-is-ai-studio.md)
+  - [Azure AI Foundry](what-is-ai-foundry.md)
   - [Plan and manage costs](./how-to/costs-plan-manage.md)

articles/ai-services/language-service/tutorials/prompt-flow.md

@@ -13,25 +13,25 @@ ms.date: 01/31/2025
 > [!IMPORTANT]
 > Some of the features described in this article might only be available in preview. This preview is provided without a service-level agreement, and we don't recommend it for production workloads. Certain features might not be supported or might have constrained capabilities. For more information, see [Supplemental Terms of Use for Microsoft Azure Previews](https://azure.microsoft.com/support/legal/preview-supplemental-terms/).
 
-[Prompt flow in Azure AI Foundry portal](../../../ai-studio/how-to/prompt-flow.md) is a development tool designed to streamline the entire development cycle of AI applications powered by Large Language Models (LLMs). You can explore and quickly start to use and fine-tune various natural language processing capabilities from Azure AI Language, reducing your time to value and deploying solutions with reliable evaluation.
+[Prompt flow in Azure AI Foundry portal](../../../ai-foundry/how-to/prompt-flow.md) is a development tool designed to streamline the entire development cycle of AI applications powered by Large Language Models (LLMs). You can explore and quickly start to use and fine-tune various natural language processing capabilities from Azure AI Language, reducing your time to value and deploying solutions with reliable evaluation.
 
 This tutorial teaches you how to use Language in prompt flow utilizing [Azure AI Foundry](https://ai.azure.com).                            
 
 ## Prerequisites
 
 - An Azure subscription - <a href="https://azure.microsoft.com/free/cognitive-services" target="_blank">Create one for free</a>.
 
-- You need an Azure AI Foundry hub or permissions to create one. Your user role must be **Azure AI Developer**, **Contributor**, or **Owner** on the hub. For more information, see [hubs](../../../ai-studio/concepts/ai-resources.md) and [Azure AI roles](../../../ai-studio/concepts/rbac-ai-studio.md).
+- You need an Azure AI Foundry hub or permissions to create one. Your user role must be **Azure AI Developer**, **Contributor**, or **Owner** on the hub. For more information, see [hubs](../../../ai-foundry/concepts/ai-resources.md) and [Azure AI roles](../../../ai-foundry/concepts/rbac-ai-foundry.md).
      - If your role is **Contributor** or **Owner**, you can [create a hub in this tutorial](#create-a-project-in-azure-ai-foundry-portal). 
      - If your role is **Azure AI Developer**, the hub must already be created. 
 
-- Your subscription needs to be below your [quota limit](../../../ai-studio/how-to/quota.md) to deploy a new flow in this tutorial.
+- Your subscription needs to be below your [quota limit](../../../ai-foundry/how-to/quota.md) to deploy a new flow in this tutorial.
 
 ## Create a project in Azure AI Foundry portal
 
 Your project is used to organize your work and save state. 
 
-[!INCLUDE [Create project](../../../ai-studio/includes/create-projects.md)]
+[!INCLUDE [Create project](../../../ai-foundry/includes/create-projects.md)]
 
 ## Using Azure AI Language via the prompt flow gallery
 

articles/ai-services/openai/how-to/content-filters.md

@@ -47,7 +47,7 @@ You can configure the following filter categories in addition to the default har
 | Protected material - text | GA| On | Completion | Identifies and blocks known text content from being displayed in the model output (for example, song lyrics, recipes, and selected web content).  |
 | Groundedness* | Preview |Off | Completion |Detects whether the text responses of large language models (LLMs) are grounded in the source materials provided by the users. Ungroundedness refers to instances where the LLMs produce information that is non-factual or inaccurate from what was present in the source materials. Requires: [Document embedding and formatting](/azure/ai-services/openai/concepts/content-filter?tabs=warning%2Cuser-prompt%2Cpython-new#embedding-documents-in-your-prompt).|
 
-[!INCLUDE [create-content-filter](../../../ai-studio/includes/create-content-filter.md)]
+[!INCLUDE [create-content-filter](../../../ai-foundry/includes/create-content-filter.md)]
 
 ## Report content filtering feedback
 

articles/ai-studio/.openpublishing.redirection.ai-studio.json

@@ -155,7 +155,16 @@
             "redirect_url": "/azure/ai-foundry/reference/region-support",
             "redirect_document_id": true
         },
-
+        {
+            "source_path_from_root": "/articles/ai-studio/index",
+            "redirect_url": "/azure/ai-foundry/index",
+            "redirect_document_id": true
+        },
+        {
+            "source_path_from_root": "/articles/ai-studio/faq.md",
+            "redirect_url": "/azure/ai-foundry/faq",
+            "redirect_document_id": true
+        },
 
         {
             "source_path_from_root": "/articles/ai-studio/responsible-use-of-ai-overview.md",

articles/machine-learning/concept-model-catalog.md

@@ -126,7 +126,7 @@ Deploying a model through MaaS allows users to get access to ready to use infere
 
 ### Fine-tune models through MaaS with Pay-as-you-go 
 
-For models that are available through MaaS and support fine-tuning, users can take advantage of hosted fine-tuning with pay-as-you-go billing to tailor the models using data they provide. For more information, see [fine-tune a Llama 2 model](/azure/ai-studio/how-to/fine-tune-model-llama) in Azure AI Foundry portal. 
+For models that are available through MaaS and support fine-tuning, users can take advantage of hosted fine-tuning with pay-as-you-go billing to tailor the models using data they provide. For more information, see [fine-tune a Llama 2 model](/azure/ai-foundry/how-to/fine-tune-model-llama) in Azure AI Foundry portal. 
 
 ### RAG with models deployed through MaaS 
 
@@ -142,7 +142,7 @@ PPay-as-you-go billing is available only to users whose Azure subscription belon
 
 [!INCLUDE [machine-learning-preview-generic-disclaimer](includes/machine-learning-preview-generic-disclaimer.md)]
 
-[!INCLUDE [content-safety-serverless-models](../ai-studio/includes/content-safety-serverless-models.md)]
+[!INCLUDE [content-safety-serverless-models](../ai-foundry/includes/content-safety-serverless-models.md)]
 
 ### Network isolation for models deployed via Serverless APIs
 

articles/machine-learning/deploy-stability-models.md

@@ -36,7 +36,7 @@ Powered by the advanced capabilities of Stable Diffusion 3.5 Large, Stable Image
 
 Stable Image Ultra supports text prompt inputs only for image generations.
 
-[!INCLUDE [models-preview](../ai-studio/includes/models-preview.md)]
+[!INCLUDE [models-preview](../ai-foundry/includes/models-preview.md)]
 
 
 ## Deploy a Stability AI model as a serverless API
@@ -151,7 +151,7 @@ The Stability AI models are deployed as a serverless API and is offered by Stabi
 
 Each time a workspace subscribes to a given model offering from Azure Marketplace, a new resource is created to track the costs associated with its consumption. The same resource is used to track costs associated with inference and fine-tuning; however, multiple meters are available to track each scenario independently.
 
-For more information on how to track costs, see [Monitor costs for models offered through the Azure Marketplace](/azure/ai-studio/how-to/costs-plan-manage#monitor-costs-for-models-offered-through-the-azure-marketplace).
+For more information on how to track costs, see [Monitor costs for models offered through the Azure Marketplace](/azure/ai-foundry/how-to/costs-plan-manage#monitor-costs-for-models-offered-through-the-azure-marketplace).
 
 Quota is managed per deployment. Each deployment has a rate limit of 200,000 tokens per minute and 1,000 API requests per minute. However, we currently limit one deployment per model per project. Contact Microsoft Azure Support if the current rate limits aren't sufficient for your scenarios.
 
@@ -163,5 +163,5 @@ Models deployed as a serverless API are protected by Azure AI content safety. Wh
 
 - [Model Catalog and Collections](concept-model-catalog.md)
 - [Deploy and score a machine learning model by using an online endpoint](how-to-deploy-online-endpoints.md)
-- [Plan and manage costs for Azure AI Foundry](/azure/ai-studio/how-to/costs-plan-manage)
+- [Plan and manage costs for Azure AI Foundry](/azure/ai-foundry/how-to/costs-plan-manage)
 - [Region availability for models in serverless API endpoints](concept-endpoint-serverless-availability.md)