add to genai capabilities

Author: gitName

articles/api-management/genai-gateway-capabilities.md

@@ -104,6 +104,16 @@ In API Management, enable semantic caching by using Azure Redis Enterprise or an
 > [!TIP]
 > To enable semantic caching for LLM APIs available through the Azure AI Model Inference API, API Management provides the equivalent [llm-semantic-cache-store-policy](llm-semantic-cache-store-policy.md) and [llm-semantic-cache-lookup-policy](llm-semantic-cache-lookup-policy.md) policies.
 
+## Azure Monitor logging
+
+Enable a [diagnostic setting](monitor-api-management.md#enable-diagnostic-setting-for-azure-monitor-logs) in your API Management instance to send logs to Azure Monitor for requests processed by the gateway for large language model REST APIs. For each request, data is logged including token usage (prompt tokens, completion tokens, and total tokens), name of the model used, and optionally the request message and response message. Large requests and responses are split into multiple log entries that are sequentially numbered for later reconstruction if needed.
+
+The API Management administrator can use LLM gateway logs along with API Management gateway logs for scenarios such as the following:
+
+* **Calculate usage for billing** - Calculate usage metrics for billing based on the number of tokens consumed by each application or API consumer (for example, segmented by subscription ID or IP address).
+* **Inspect messages** - Inspect and analyze prompts and completions for debugging or auditing.
+
+Learn more about [monitoring API Management with Azure Monitor](monitor-api-management.md).
 
 ## Labs and samples
 

articles/api-management/visual-studio-code-tutorial.md

@@ -5,7 +5,7 @@ ms.service: azure-api-management
 author: dlepow
 ms.author: danlep
 ms.topic: tutorial
-ms.date: 02/24/2025
+ms.date: 02/20/2025
 ms.custom: devdivchpfy22
 ---