答案：A  🗳️

說明：（僅 Fast2test 成員可見）

答案：

Explanation:

Explanation:
curl -i -X: The POST method is appropriate because you are creating a new custom analyzer, which involves sending a request to create a resource. POST is used for creating new resources in REST APIs.
https:// < cu1 > .services.ai.azure.com/: The base URL should be updated to include the contentunderstanding endpoint, as this is the specific service within the Azure AI Content Understanding resource (cu1) that handles analyzer-related operations. Replace < cu1 > with the actual resource name or endpoint provided by your Azure subscription.
/analyzers/myInvoice7api-version-2024-12-01-preview: This part of the URL is correct as it specifies the endpoint for creating a custom analyzer (/analyzers) with the name myInvoice7 and the API version 2024-12-
01-preview. No changes are needed here, assuming the analyzer name and version are intended as shown.

答案：

Explanation:

The question describes:
An Azure subscription with an Azure AI Content Safety resource.
A social media application where users can upload images.
The requirement is to moderate inappropriate content in those uploaded images.
In Azure AI Content Safety SDKs:
You create a ContentSafetyClient by providing the endpoint and key.
The ContentSafetyClient exposes methods such as:
AnalyzeText() # For text moderation
AnalyzeImage() # For image moderation
Let's review the code structure:
public static void Analyze ( AnalyzeImageOptions request )
{
var endpoint = Environment.GetEnvironmentVariable( " ENDPOINT " );
var key = Environment.GetEnvironmentVariable( " KEY " );
var client = new ContentSafetyClient( new Uri(endpoint), new AzureKeyCredential(key)); return client.AnalyzeImage(request);
}
First dropdown: must be ContentSafetyClient to instantiate the correct client for Azure AI Content Safety.
Second dropdown: since the requirement is image moderation, we must call client.AnalyzeImage(request) .
Other options:
BlocklistClient # used for custom blocklists, not full moderation.
TextCategoriesAnalysis # refers to text analysis categories, not suitable here.
AnalyzeText # would be used only for text moderation.
Therefore, the correct completion is:
ContentSafetyClient
client.AnalyzeImage(request)
The answer:
First dropdown: ContentSafetyClient
Second dropdown: client.AnalyzeImage(request)
Microsoft References
Azure AI Content Safety - Analyze images
Azure AI Content Safety SDK documentation
ContentSafetyClient class

答案：

Explanation:

Code Recap (Custom Skill JSON Schema)
{
" @odata.type " : " #Microsoft.Skills.Custom.WebApiSkill " ,
" description " : " My custom skill description " ,
" uri " : " https://contoso-webskill.azurewebsites.net/api/process " ,
" context " : " /document/organizations/* " ,
" inputs " : [
{
" name " : " companyName " ,
" source " : " /document/organizations/* "
}
],
" outputs " : [
{
" name " : " companyDescription "
}
]
}
Statement Analysis
CompanyDescription is available for indexing.
Yes.
The skill produces an output field called companyDescription . Outputs of a custom skill become part of the enrichment tree, which can then be projected into the search index or knowledge store.
The definition calls a web API as part of the enrichment process.
Yes.
This is a Web API skill ( @odata.type: #Microsoft.Skills.Custom.WebApiSkill ) with a uri pointing to
https://contoso-webskill.azurewebsites.net/api/process . This means an external web API is called to enrich data.
The enrichment step is called only for the first organization under /document/organizations .
No.
The context is set to " /document/organizations/* " , where the * means the skill runs for each element in the collection. It is not limited to the first element.
Final Answer
CompanyDescription is available for indexing # Yes
The definition calls a web API as part of the enrichment process # Yes
The enrichment step is called only for the first organization under /document/organizations # No Microsoft References Custom skills in Azure Cognitive Search Enrichment tree and skill context Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-output-field-mapping