work in progress

Author: dlepow

articles/api-management/azure-ai-foundry-api.md

@@ -0,0 +1,99 @@
+---
+title: Import an Azure AI Foundry API - Azure API Management
+description: How to import an API from Azure AI Foundry as a REST API in Azure API Management.
+ms.service: azure-api-management
+author: dlepow
+ms.author: danlep
+ms.topic: how-to
+ms.date: 05/15/2025
+ms.collection: ce-skilling-ai-copilot
+ms.custom: template-how-to, build-2024
+---
+
+# Import an LLM API 
+
+[!INCLUDE [api-management-availability-all-tiers](../../includes/api-management-availability-all-tiers.md)]
+
+[INTRO]
+
+Learn more about managing AI APIs in API Management:
+
+* [Generative AI gateway capabilities in Azure API Management](genai-gateway-capabilities.md)
+
+
+## AI service options
+* **Azure OpenAI service** - Deployment name of a model is passed in the URL path of the API request.
+
+* **Azure AI** - These are models that are available in Azure AI Foundry through the [Azure AI Model Inference API](/azure/ai-studio/reference/reference-model-inference-api). Deployment name of a model is passed in the request body of the API request. 
+
+
+## Prerequisites
+
+- An existing API Management instance. [Create one if you haven't already](get-started-create-service-instance.md).
+- One or more Azure AI services with models deployed, such as:
+    - An Azure OpenAI resource. For information about model deployment in Azure OpenAI service, see the [resource deployment guide](/azure/ai-services/openai/how-to/create-resource).
+    -  An Azure AI Foundry project. For information about creating a project, see [Create a project in the Azure AI Foundry portal](/azure/ai-foundry/how-to/create-projects). 
+    
+
+
+## Import AI Foundry API using the portal
+
+Use the following steps to import an AI Foundry API directly to API Management. 
+
+[!INCLUDE [api-management-workspace-availability](../../includes/api-management-workspace-availability.md)]
+
+When you import the API, API Management automatically configures:
+
+* Operations for each of the API's REST API endpoints
+* A system-assigned identity with the necessary permissions to access the AI service deployment.
+* A [backend](backends.md) resource and a [set-backend-service](set-backend-service-policy.md) policy that direct API requests to the AI service endpoint.
+* Authentication to the backend using the instance's system-assigned managed identity.
+* (optionally) Policies to help you monitor and manage the API.
+
+To import an AI Foundry API to API Management:
+
+1. In the [Azure portal](https://portal.azure.com), navigate to your API Management instance.
+1. In the left menu, under **APIs**, select **APIs** > **+ Add API**.
+1. Under **Create from Azure resource**, select **Azure AI Foundry**.
+
+    :::image type="content" source="media/azure-ai-foundry-api/ai-foundry-api.png" alt-text="Screenshot of creating an OpenAI-compatible API in the portal." :::
+1. On the **Select AI service** tab:
+    1. Select the **Subscription** in which to search for AI services (Azure OpenAI services or Azure AI Foundry projects). To get information about the deployments in a service, select the **deployments** link next to the service name.
+       :::image type="content" source="media/azure-ai-foundry-api/deployments.png" alt-text="Screenshot of deployments for an AI service in the portal.":::
+    1. Select an AI service. 
+    1. Select **Next**.
+1. On the **Configure API** tab:
+    1. Enter a **Display name** and optional **Description** for the API.
+    1. In **Path**, enter a path that your API Management instance uses to access the API endpoints.
+    1. Optionally select one or more **Products** to associate with the API.  
+    1. In **Client compatibility**, select either of the following based on the types of client you intend to support:
+        * **Azure OpenAI** - Clients call the model deployment using the OpenAI API format. Select this option if you use only Azure OpenAI deployments.
+        * **Azure AI** - Clients call the model deployment by passing 
+    1. In **Access key**, optionally enter the authorization header name and API key used to access the LLM API. 
+    1. Select **Next**.
+1. On the **Manage token consumption** tab, optionally enter settings or accept defaults that define the following policies to help monitor and manage the API:
+    * [Manage token consumption](llm-token-limit-policy.md)
+    * [Track token usage](llm-emit-token-metric-policy.md) 
+1. On the **Apply semantic caching** tab, optionally enter settings or accept defaults that define the policies to help optimize performance and reduce latency for the API:
+    * [Enable semantic caching of responses](azure-openai-enable-semantic-caching.md)
+On the **AI content safety**, optionally enter settings or accept defaults to configure the Azure AI Content Safety service checks for API requests:
+    * [Enforce content safety checks on LLM requests](llm-content-safety-policy.md)
+1. Select **Review**.
+1. After settings are validated, select **Create**. 
+
+## Test the LLM API
+
+To ensure that your LLM API is working as expected, test it in the API Management test console. 
+1. Select the API you created in the previous step.
+1. Select the **Test** tab.
+1. Select an operation that's compatible with the model in the LLM API.
+    The page displays fields for parameters and headers.
+1. Enter parameters and headers as needed. Depending on the operation, you may need to configure or update a **Request body**.
+    > [!NOTE]
+    > In the test console, API Management automatically populates an **Ocp-Apim-Subscription-Key** header, and configures the subscription key of the built-in [all-access subscription](api-management-subscriptions.md#all-access-subscription). This key enables access to every API in the API Management instance. Optionally display the **Ocp-Apim-Subscription-Key** header by selecting the "eye" icon next to the **HTTP Request**.
+1. Select **Send**.
+
+    When the test is successful, the backend responds with a successful HTTP response code and some data. Appended to the response is token usage data to help you monitor and manage your Azure OpenAI API token consumption.
+
+
+[!INCLUDE [api-management-define-api-topics.md](../../includes/api-management-define-api-topics.md)]

articles/api-management/azure-openai-api-from-specification.md

@@ -26,7 +26,7 @@ Learn more about managing AI APIs in API Management:
 ## Prerequisites
 
 - An existing API Management instance. [Create one if you haven't already](get-started-create-service-instance.md).
-- An Azure OpenAI resource with a model deployed. For more information about model deployment, see the [resource deployment guide](/azure/ai-services/openai/how-to/create-resource).
+- An Azure OpenAI resource with a model deployed. For more information about model deployment in Azure OpenAI service, see the [resource deployment guide](/azure/ai-services/openai/how-to/create-resource).
 
     Make a note of the ID (name) of the deployment. You'll need it when you test the imported API in API Management.
 

articles/api-management/media/azure-ai-foundry-api/ai-foundry-api.png

@@ -1,16 +1,16 @@
 ---
-title: Import an LLM API as REST API - Azure API Management
-description: How to import an OpenAI-compatible LLM API or other AI model as a REST API in Azure API Management.
+title: Import a Language Model API as REST API - Azure API Management
+description: How to import an OpenAI-compatible language model API or other AI model as a REST API in Azure API Management.
 ms.service: azure-api-management
 author: dlepow
 ms.author: danlep
 ms.topic: how-to
-ms.date: 05/14/2025
+ms.date: 05/15/2025
 ms.collection: ce-skilling-ai-copilot
 ms.custom: template-how-to, build-2024
 ---
 
-# Import an LLM API 
+# Import a language model API 
 
 [!INCLUDE [api-management-availability-all-tiers](../../includes/api-management-availability-all-tiers.md)]
 
@@ -23,20 +23,20 @@ Learn more about managing AI APIs in API Management:
 ## Prerequisites
 
 - An existing API Management instance. [Create one if you haven't already](get-started-create-service-instance.md).
-- A self-hosted LLM with an API endpoint. You can use an OpenAI-compatible LLM that's exposed by an inference provider such as [Hugging Face Text Generation Inference (TGI)](hhttps://huggingface.co/docs/text-generation-inference/en/index). Alternatively, you can access an LLM through a provider such as [Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
+- A self-hosted LLM with an API endpoint. You can use an OpenAI-compatible LLM that's exposed by an inference provider such as [Hugging Face Text Generation Inference (TGI)](https://huggingface.co/docs/text-generation-inference/en/index). Alternatively, you can access an LLM through a provider such as [Amazon Bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html).
     > [!NOTE]
     > API Management policies such as [llm-token-limit](llm-token-limit-policy.md) and [llm-emit-token-metric](llm-emit-token-metric-policy.md) are supported for APIs available through the [Azure AI Model Inference API](/azure/ai-studio/reference/reference-model-inference-api) or with OpenAI-compatible models served through third-party inference providers.
 
 
-## Import LLM API using the portal
+## Import language model API using the portal
 
-Jse the following steps to import an LLM API directly to API Management. 
+Use the following steps to import an LLM API directly to API Management. 
 
 [!INCLUDE [api-management-workspace-availability](../../includes/api-management-workspace-availability.md)]
 
 Depending on the API type you select to import, API Management automatically configures different operations to call the API: 
 
-* **OpenAI-compatible API** - Operations for the LLM API's chat completion endpoint
+* **OpenAI-compatible API** - An operation for the LLM API's chat completion endpoint
 * **Passthrough API** - Wildcard operations for standard verbs `GET`, `HEAD`, `OPTIONS`, and `TRACK`. When you call the API, append any required path or parameters to the API request to pass a request to an LLM API endpoint.
 
 For an OpenAI-compatible API, you can optionally configure policies to help you monitor and manage the API.
@@ -45,28 +45,28 @@ To import an LLM API to API Management:
 
 1. In the [Azure portal](https://portal.azure.com), navigate to your API Management instance.
 1. In the left menu, under **APIs**, select **APIs** > **+ Add API**.
-1. Under **Define a new API**, select **OpenAI API**.
+1. Under **Define a new API**, select **Language Model API**.
 
     :::image type="content" source="media/openai-compatible-llm-api/openai-api.png" alt-text="Screenshot of creating an OpenAI-compatible API in the portal." :::
 
 1. On the **Configure API** tab:
     1. Enter a **Display name** and optional **Description** for the API.
     1. Enter the **URL** to the LLM API endpoint.
-    1. Optionally select one or more **Products**l to associate with the API.  
+    1. Optionally select one or more **Products** to associate with the API.  
     1. In **Path**, append a path that your API Management instance uses to access the LLM API endpoints.
     1. In **Type**, select either **Create OpenAI API** or **Create a passthrough API**.   
     1. In **Access key**, optionally enter the authorization header name and API key used to access the LLM API. 
     1. Select **Next**.
 1. On the **Manage token consumption** tab, optionally enter settings or accept defaults that define the following policies to help monitor and manage the API:
     * [Manage token consumption](llm-token-limit-policy.md)
-    * [Track token usage](llm-token-metric-policy.md) 
+    * [Track token usage](llm-emit-token-metric-policy.md) 
 1. On the **Apply semantic caching** tab, optionally enter settings or accept defaults that define the policies to help optimize performance and reduce latency for the API:
     * [Enable semantic caching of responses](azure-openai-enable-semantic-caching.md)
-1. On the **AI content safety**, optionally enter settings or accept defaults to configure [Azure AI Content Safety](llm-content-safety-policy.md) for the API. 
+1. On the **AI content safety**, optionally enter settings or accept defaults to configure the Azure AI Content Safety service checks for API requests:
+    * [Enforce content safety checks on LLM requests](llm-content-safety-policy.md)
 1. Select **Review**.
 1. After settings are validated, select **Create**. 
 
-
 ## Test the LLM API
 
 To ensure that your LLM API is working as expected, test it in the API Management test console.