Merge pull request #261476 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)

Author: Taojunshen

articles/ai-services/openai/includes/use-your-data-go.md

@@ -36,91 +36,86 @@ ms.date: 08/29/2023
    package main
 
    import (
-       "context"
-       "fmt"
-       "log"
-       "os"
-
-       "github.com/Azure/azure-sdk-for-go/sdk/ai/azopenai"
-       "github.com/Azure/azure-sdk-for-go/sdk/azcore/to"
+   	"context"
+   	"fmt"
+   	"log"
+   	"os"
+   
+   	"github.com/Azure/azure-sdk-for-go/sdk/ai/azopenai"
+   	"github.com/Azure/azure-sdk-for-go/sdk/azcore"
+   	"github.com/Azure/azure-sdk-for-go/sdk/azcore/to"
    )
-
+   
    func main() {
-       azureOpenAIKey := os.Getenv("AOAIKey")
-       modelDeploymentID := os.Getenv("AOAIDeploymentId")
-
-       // Ex: "https://<your-azure-openai-host>.openai.azure.com"
-       azureOpenAIEndpoint := os.Getenv("AOAIEndpoint")
-
-       // Azure AI Search configuration
-       searchIndex := os.Getenv("SearchIndex")
-       searchEndpoint := os.Getenv("SearchEndpoint")
-       searchAPIKey := os.Getenv("SearchKey")
-
-       if azureOpenAIKey == "" || modelDeploymentID == "" || azureOpenAIEndpoint == "" || searchIndex == "" || searchEndpoint == "" || searchAPIKey == "" {
-           fmt.Fprintf(os.Stderr, "Skipping example, environment variables missing\n")
-           return
-       }
-
-       keyCredential, err := azopenai.NewKeyCredential(azureOpenAIKey)
-
-       if err != nil {
-           //  TODO: Update the following line with your application specific error handling logic
-           log.Fatalf("ERROR: %s", err)
-       }
-
-       // In Azure OpenAI you must deploy a model before you can use it in your client. For more information
-       // see here: https://learn.microsoft.com/azure/cognitive-services/openai/how-to/create-resource
-       client, err := azopenai.NewClientWithKeyCredential(azureOpenAIEndpoint, keyCredential, nil)
-
-       if err != nil {
-           //  TODO: Update the following line with your application specific error handling logic
-           log.Fatalf("ERROR: %s", err)
-       }
-
-       resp, err := client.GetChatCompletions(context.TODO(), azopenai.ChatCompletionsOptions{
-           Messages: []azopenai.ChatMessage{
-               {Content: to.Ptr("What are the differences between Azure Machine Learning and Azure AI services?"), Role: to.Ptr(azopenai.ChatRoleUser)},
-           },
-           MaxTokens: to.Ptr[int32](512),
-           AzureExtensionsOptions: &azopenai.AzureChatExtensionOptions{
-               Extensions: []azopenai.AzureChatExtensionConfiguration{
-                   {
-                       // This allows Azure OpenAI to use an Azure AI Search index.
-                       //
-                       // > Because the model has access to, and can reference specific sources to support its responses, answers are not only based on its pretrained knowledge
-                       // > but also on the latest information available in the designated data source. This grounding data also helps the model avoid generating responses
-                       // > based on outdated or incorrect information.
-                       //
-                       // Quote from here: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/use-your-data
-                       Type: to.Ptr(azopenai.AzureChatExtensionTypeAzureCognitiveSearch),
-                       Parameters: azopenai.AzureCognitiveSearchChatExtensionConfiguration{
-                           Endpoint:  &searchEndpoint,
-                           IndexName: &searchIndex,
-                           Key:       &searchAPIKey,
-                       },
-                   },
-               },
-           },
-           Deployment: modelDeploymentID,
-       }, nil)
-
-       if err != nil {
-       //  TODO: Update the following line with your application specific error handling logic
-       log.Fatalf("ERROR: %s", err)
-   }
-
-   // Contains contextual information from your Azure chat completion extensions, configured above in `AzureExtensionsOptions`
-   msgContext := resp.Choices[0].Message.Context
-
-       fmt.Fprintf(os.Stderr, "Extensions Context Role: %s\nExtensions Context (length): %d\n",
-           *msgContext.Messages[0].Role,
-           len(*msgContext.Messages[0].Content))
-
-       fmt.Fprintf(os.Stderr, "ChatRole: %s\nChat content: %s\n",
-           *resp.Choices[0].Message.Role,
-           *resp.Choices[0].Message.Content,
-       )
+   	azureOpenAIKey := os.Getenv("AOAIKey")
+   	modelDeploymentID := os.Getenv("AOAIDeploymentId")
+   
+   	// Ex: "https://<your-azure-openai-host>.openai.azure.com"
+   	azureOpenAIEndpoint := os.Getenv("AOAIEndpoint")
+   
+   	// Azure AI Search configuration
+   	searchIndex := os.Getenv("SearchIndex")
+   	searchEndpoint := os.Getenv("SearchEndpoint")
+   	searchAPIKey := os.Getenv("SearchKey")
+   
+   	if azureOpenAIKey == "" || modelDeploymentID == "" || azureOpenAIEndpoint == "" || searchIndex == "" || searchEndpoint == "" || searchAPIKey == "" {
+   		fmt.Fprintf(os.Stderr, "Skipping example, environment variables missing\n")
+   		return
+   	}
+   
+   	keyCredential := azcore.NewKeyCredential(azureOpenAIKey)
+   
+   	// In Azure OpenAI you must deploy a model before you can use it in your client. For more information
+   	// see here: https://learn.microsoft.com/azure/cognitive-services/openai/how-to/create-resource
+   	client, err := azopenai.NewClientWithKeyCredential(azureOpenAIEndpoint, keyCredential, nil)
+   
+   	if err != nil {
+   		//  TODO: Update the following line with your application specific error handling logic
+   		log.Fatalf("ERROR: %s", err)
+   	}
+   
+   	resp, err := client.GetChatCompletions(context.TODO(), azopenai.ChatCompletionsOptions{
+   		Messages: []azopenai.ChatRequestMessageClassification{
+   			&azopenai.ChatRequestUserMessage{Content: azopenai.NewChatRequestUserMessageContent("What are the differences between Azure Machine Learning and Azure AI services?")},
+   		},
+   		MaxTokens: to.Ptr[int32](512),
+   		AzureExtensionsOptions: []azopenai.AzureChatExtensionConfigurationClassification{
+   			&azopenai.AzureCognitiveSearchChatExtensionConfiguration{
+   				// This allows Azure OpenAI to use an Azure AI Search index.
+   				//
+   				// > Because the model has access to, and can reference specific sources to support its responses, answers are not only based on its pretrained knowledge
+   				// > but also on the latest information available in the designated data source. This grounding data also helps the model avoid generating responses
+   				// > based on outdated or incorrect information.
+   				//
+   				// Quote from here: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/use-your-data
+   				Parameters: &azopenai.AzureCognitiveSearchChatExtensionParameters{
+   					Endpoint:  &searchEndpoint,
+   					IndexName: &searchIndex,
+   					Authentication: &azopenai.OnYourDataAPIKeyAuthenticationOptions{
+   						Key: &searchAPIKey,
+   					},
+   				},
+   			},
+   		},
+   		DeploymentName: &modelDeploymentID,
+   	}, nil)
+   
+   	if err != nil {
+   		//  TODO: Update the following line with your application specific error handling logic
+   		log.Fatalf("ERROR: %s", err)
+   	}
+   
+   	// Contains contextual information from your Azure chat completion extensions, configured above in `AzureExtensionsOptions`
+   	msgContext := resp.Choices[0].Message.Context
+   
+   	fmt.Fprintf(os.Stderr, "Extensions Context Role: %s\nExtensions Context (length): %d\n",
+   		*msgContext.Messages[0].Role,
+   		len(*msgContext.Messages[0].Content))
+   
+   	fmt.Fprintf(os.Stderr, "ChatRole: %s\nChat content: %s\n",
+   		*resp.Choices[0].Message.Role,
+   		*resp.Choices[0].Message.Content,
+   	)
    }
    ```
 
@@ -136,4 +131,4 @@ ms.date: 08/29/2023
    The application prints the response including both answers to your query and citations from your uploaded files.
 
 > [!div class="nextstepaction"]
-> [I ran into an issue when running the code samples.](https://microsoft.qualtrics.com/jfe/form/SV_0Cl5zkG3CnDjq6O?PLanguage=dotnet&Pillar=AOAI&Product=ownData&Page=quickstart&Section=Create-dotnet-application)
+> [I ran into an issue when running the code samples.](https://microsoft.qualtrics.com/jfe/form/SV_0Cl5zkG3CnDjq6O?PLanguage=dotnet&Pillar=AOAI&Product=ownData&Page=quickstart&Section=Create-dotnet-application)

articles/azure-functions/functions-reference-python.md

@@ -973,7 +973,7 @@ pip install -r requirements.txt
 
 When running your functions in an [App Service plan](./dedicated-plan.md), dependencies that you define in requirements.txt are given precedence over built-in Python modules, such as `logging`. This precedence can cause conflicts when built-in modules have the same names as directories in your code. When running in a [Consumption plan](./consumption-plan.md) or an [Elastic Premium plan](./functions-premium-plan.md), conflicts are less likely because your dependencies aren't prioritized by default. 
 
-To prevent issues running in an App Service plan, don't name your directories the same as any Python native modules and don't including Python native libraries in your project's requirements.txt file.
+To prevent issues running in an App Service plan, don't name your directories the same as any Python native modules and don't include Python native libraries in your project's requirements.txt file.
 
 ## Publishing to Azure
 

articles/container-registry/container-registry-tasks-overview.md

@@ -82,7 +82,7 @@ The power of ACR Tasks to truly enhance your container build workflow comes from
 You can set up an ACR task to track a dependency on a base image when it builds an application image. When the updated base image is pushed to your registry, or a base image is updated in a public repo such as in Docker Hub, ACR Tasks can automatically build any application images based on it.
 With this automatic detection and rebuilding, ACR Tasks saves you the time and effort normally required to manually track and update each and every application image referencing your updated base image.
 
-Learn more about [base image update triggers](container-registry-tasks-base-images.md) for ACR Tasks. And learn how to trigger an image build when a base image is pushed to a container registry in the tutorial [Automate container image builds when a base image is updated in a Azure container registry](container-registry-tutorial-base-image-update.md)
+Learn more about [base image update triggers](container-registry-tasks-base-images.md) for ACR Tasks. And learn how to trigger an image build when a base image is pushed to a container registry in the tutorial [Automate container image builds when a base image is updated in an Azure container registry](container-registry-tutorial-base-image-update.md)
 
 ## Schedule a task
 

articles/defender-for-cloud/alert-validation.md

@@ -79,7 +79,7 @@ Alternately, you can also use the [EICAR](https://www.eicar.org/download-anti-ma
 After the Microsoft Defender for Endpoint agent is installed on your machine, as part of Defender for Servers integration, follow these steps from the machine where you want to be the attacked resource of the alert:
 
 1. Open a Terminal window, copy and run the following command:
-`curl -o ~/Downloads/eicar.com.txt`
+`curl -O https://secure.eicar.org/eicar.com.txt`
 
 1. The Command Prompt window closes automatically. If successful, a new alert should appear in Defender for Cloud Alerts blade in 10 minutes.
 

articles/private-link/tutorial-private-endpoint-sql-powershell.md

@@ -20,7 +20,7 @@ In this tutorial, you learn how to:
 > [!div class="checklist"]
 > * Create a virtual network and bastion host.
 > * Create a virtual machine.
-> * Create a Azure SQL server and private endpoint.
+> * Create an Azure SQL server and private endpoint.
 > * Test connectivity to the SQL server private endpoint.
 
 ## Prerequisites

articles/vpn-gateway/about-vpn-profile-download.md

@@ -52,7 +52,7 @@ In the **AzureVPN** folder, go to the ***azurevpnconfig.xml*** file and open it
 ```
 <audience>          </audience>
 <issuer>            </issuer>
-<tennant>           </tennant>
+<tenant>            </tenant>
 <fqdn>              </fqdn>
 <serversecret>      </serversecret>
 ```