Merge pull request #262824 from mrbullwinkle/mrb_01_09_2024_keyword_quotes

[Azure OpenAI] GitHub Issue

Author: prmerger-automator[bot]

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"]  
 )
 
 
@@ -111,7 +111,10 @@ client = AzureOpenAI(
 
 ## Keyword argument for model
 
-OpenAI uses the `model` keyword argument to specify what model to use. Azure OpenAI has the concept of unique model [deployments](create-resource.md?pivots=web-portal#deploy-a-model). When using Azure OpenAI `model` should refer to the underling deployment name you chose when you deployed the model. 
+OpenAI uses the `model` keyword argument to specify what model to use. Azure OpenAI has the concept of unique model [deployments](create-resource.md?pivots=web-portal#deploy-a-model). When using Azure OpenAI `model` should refer to the underlying deployment name you chose when you deployed the model.
+
+> [!IMPORTANT]
+> When you access the model via the API in Azure OpenAI 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 are 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.
 
 <table>
 <tr>
@@ -122,7 +125,7 @@ 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 +145,7 @@ 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 are 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

@@ -100,25 +100,28 @@ To deploy a model, follow these steps:
 
 1. Sign in to [Azure OpenAI Studio](https://oai.azure.com).
 
-1. Choose the subscription and the Azure OpenAI resource to work with, and select **Use resource**.
+2. Choose the subscription and the Azure OpenAI resource to work with, and select **Use resource**.
 
-1. Under **Management** select **Deployments**.
+3. Under **Management** select **Deployments**.
 
-1. Select **Create new deployment** and configure the following fields:
+4. Select **Create new deployment** and configure the following fields:
 
    | Field | Description |
    |---|---|
    | **Select a model** | Model availability varies by region. For a list of available models per region, see [Model summary table and region availability](../concepts/models.md#model-summary-table-and-region-availability). |
    | **Deployment name** | Choose a name carefully. The deployment name is used in your code to call the model by using the client libraries and the REST APIs. |
    | **Advanced options** (Optional) | You can set optional advanced settings, as needed for your resource. <br> - For the **Content Filter**, assign a content filter to your deployment.<br> - For the **Tokens per Minute Rate Limit**, adjust the Tokens per Minute (TPM) to set the effective rate limit for your deployment. You can modify this value at any time by using the [**Quotas**](../how-to/quota.md) menu. |
 
-   1. Select a model from the dropdown list.
+5. Select a model from the dropdown list.
 
-   1. Enter a deployment name to help you identify the model.
+6. Enter a deployment name to identify the model.
 
-   1. For your first deployment, leave the **Advanced options** set to the defaults.
+    > [!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 are 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. Select **Create**.
+7. For your first deployment, leave the **Advanced options** set to the defaults.
+
+8. Select **Create**.
 
 The deployments table shows a new entry that corresponds to your newly created model.
 

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 are 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.