Merge pull request #4532 from MicrosoftDocs/main

05/05/2025 AM Publishing

Author: v-alje

articles/ai-foundry/model-inference/includes/use-embeddings/python.md

@@ -52,7 +52,7 @@ If you have configured the resource to with **Microsoft Entra ID** support, you
 ```python
 import os
 from azure.ai.inference import EmbeddingsClient
-from azure.core.credentials import AzureKeyCredential
+from azure.identity import DefaultAzureCredential
 
 model = EmbeddingsClient(
     endpoint=os.environ["AZURE_INFERENCE_ENDPOINT"],

articles/ai-services/openai/how-to/dynamic-quota.md

@@ -60,7 +60,7 @@ Alternatively, you can enable it programmatically with Azure CLI's [`az rest`](/
 Replace the `{subscriptionId}`, `{resourceGroupName}`, `{accountName}`, and `{deploymentName}` with the relevant values for your resource. In this case, `accountName` is equal to Azure OpenAI resource name.
 
 ```azurecli
-az rest --method patch --url "https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/deployments/{deploymentName}?2023-10-01-preview" --body '{"properties": {"dynamicThrottlingEnabled": true} }'
+az rest --method patch --url "https://management.azure.com/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{accountName}/deployments/{deploymentName}?api-version=2023-10-01-preview" --body '{"properties": {"dynamicThrottlingEnabled": true} }'
 ```
 
 ### How do I know how much throughput dynamic quota is adding to my app?

articles/machine-learning/how-to-deploy-mlflow-models-online-endpoints.md

@@ -10,7 +10,7 @@ ms.author: mopeakande
 ms.reviewer: fasantia
 ms.date: 03/31/2025
 ms.topic: how-to
-ms.custom: deploy, mlflow, devplatv2, no-code-deployment, devx-track-azurecli, cliv2, update-code
+ms.custom: deploy, mlflow, devplatv2, no-code-deployment, devx-track-azurecli, cliv2, update-code1
 # customer intent: As a developer, I want to see how to deploy an MLflow model to an online endpoint so that I can use the model to make predictions in real time.
 ---