update

Author: mrbullwinkle

articles/ai-services/openai/how-to/switching-endpoints.md

@@ -34,7 +34,7 @@ We recommend using environment variables. If you haven't done this before our [P
 from openai import OpenAI
 
 client = OpenAI(
-  api_key=os.environ['OPENAI_API_KEY']  
+  api_key=os.environ["OPENAI_API_KEY"]  
 )
 
 
@@ -74,7 +74,7 @@ client = AzureOpenAI(
 from openai import OpenAI
 
 client = OpenAI(
-  api_key=os.environ['OPENAI_API_KEY']  
+  api_key=os.environ["OPENAI_API_KEY"]  
 )
 
 
@@ -122,7 +122,7 @@ OpenAI uses the `model` keyword argument to specify what model to use. Azure Ope
 
 ```python
 completion = client.completions.create(
-    model='gpt-3.5-turbo-instruct',
+    model="gpt-3.5-turbo-instruct",
     prompt="<prompt>")
 )
 
@@ -142,7 +142,7 @@ embedding = client.embeddings.create(
 
 ```python
 completion = client.completions.create(
-    model=gpt-35-turbo-instruct, # This must match the custom deployment name you chose for your model.
+    model="gpt-35-turbo-instruct", # This must match the custom deployment name you chose for your model.
     prompt=<"prompt">
 )
 

articles/ai-services/openai/includes/create-resource-cli.md

@@ -95,6 +95,9 @@ az cognitiveservices account deployment create \
 --sku-name "Standard"
 ```
 
+> [!IMPORTANT]
+> When you access the model via the API you will need to refer to the deployment name rather than the underlying model name in API calls. This is one of the [key differences](../how-to/switching-endpoints.md) between OpenAI and Azure OpenAI. OpenAI only requires the model name, Azure OpenAI always requires deployment name, even when using the model parameter. In our docs we often have examples where deployment names is represented as identical to model names to help indicate which model works with a particular API endpoint. Ultimately your deployment names can follow whatever naming convention is best for your use case.
+
 ## Delete a model from your resource
 
 You can delete any model deployed from your resource with the [az cognitiveservices account deployment delete](/cli/azure/cognitiveservices/account/deployment?view=azure-cli-latest&preserve-view=true#az-cognitiveservices-account-deployment-delete) command. In the following example, you delete a model named _MyModel_. When you try the example, update the code to use your values for the resource group, resource, and deployed model. 

articles/ai-services/openai/includes/create-resource-portal.md

@@ -114,7 +114,10 @@ To deploy a model, follow these steps:
 
    1. Select a model from the dropdown list.
 
-   1. Enter a deployment name to help you identify the model.
+   1. Enter a deployment name to identify the model.
+
+    > [!IMPORTANT]
+    > When you access the model via the API you will need to refer to the deployment name rather than the underlying model name in API calls. This is one of the [key differences](../how-to/switching-endpoints.md) between OpenAI and Azure OpenAI. OpenAI only requires the model name, Azure OpenAI always requires deployment name, even when using the model parameter. In our docs we often have examples where deployment names is represented as identical to model names to help indicate which model works with a particular API endpoint. Ultimately your deployment names can follow whatever naming convention is best for your use case.
 
    1. For your first deployment, leave the **Advanced options** set to the defaults.
 

articles/ai-services/openai/includes/create-resource-powershell.md

@@ -90,6 +90,9 @@ $sku = New-Object -TypeName "Microsoft.Azure.Management.CognitiveServices.Models
 New-AzCognitiveServicesAccountDeployment -ResourceGroupName OAIResourceGroup -AccountName MyOpenAIResource -Name MyModel -Properties $properties -Sku $sku
 ```
 
+> [!IMPORTANT]
+> When you access the model via the API you will need to refer to the deployment name rather than the underlying model name in API calls. This is one of the [key differences](../how-to/switching-endpoints.md) between OpenAI and Azure OpenAI. OpenAI only requires the model name, Azure OpenAI always requires deployment name, even when using the model parameter. In our docs we often have examples where deployment names is represented as identical to model names to help indicate which model works with a particular API endpoint. Ultimately your deployment names can follow whatever naming convention is best for your use case.
+
 ## Delete a model from your resource
 
 You can delete any model deployed from your resource with the [Remove-AzCognitiveServicesAccountDeployment](/powershell/module/az.cognitiveservices/remove-azcognitiveservicesaccountdeployment) command. In the following example, you delete a model named _MyModel_. When you try the example, update the code to use your values for the resource group, resource, and deployed model.