Explanation:

You are building an application that:
* Uses Azure Translator service to translate text.
* The text comes from getTextToBeTranslated().
* The text can be in many languages.
* Requirement: the content must remain within the Americas Azure geography.
* Output: must translate text into a single language (English in this case).
* The Translator service provides region-specific endpoints.
* For Americas geography, you must use the North America (NAM) endpoint:
* https://api-nam.cognitive.microsofttranslator.com/translate
* Other options like api-apc (Asia Pacific) or api-nam.../detect are incorrect because:
* /detect is used to identify the source language, not translate.
* /transliterate is for script conversion, not translation.
* We need the /translate path.
* To specify the target language, you must use the to query string parameter. Example:
* ?to=en
* Options like from=en or suggestedFrom=en are not correct here, because:
* The text can be in many languages # we don't know the source language in advance.
* Translator automatically detects the source if from is not specified.
* We only need to define the target language.
var endpoint = "https://api-nam.cognitive.microsofttranslator.com/translate"; var apiKey = "YOUR_SUBSCRIPTION_KEY"; var text = getTextToBeTranslated(); var body = "[{'Text':'" + text + "'}]"; var client = new HttpClient(); client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", apiKey); var uri = endpoint + "?to=en"; HttpResponseMessage response; var content = new StringContent(body, Encoding.UTF8, "application/json"); response = await client.PutAsync(uri, content);
* Endpoint: https://api-nam.cognitive.microsofttranslator.com/translate
* URI: ?to=en
* Translator v3.0 Reference
* Region-specific Translator endpoints

Explanation:
Use "definition" for the first field and "sampleBlobUrl" for the second field When creating a custom text category in Azure AI Content Safety, you call the PUT /contentsafety/text
/categories/{categoryName} endpoint and provide a JSON body that includes:
* categoryName: the identifier of your category.
* definition: a natural-language description of what the category covers (e.g., "text prompts about learning advice while preparing for an exam").
* sampleBlobUrl: a pointer to labeled sample data (typically a JSONL file in Azure Storage) used to help the service understand the category.
Keys like prompt or text are used when analyzing content (for example, text:detect), not when defining a category. Likewise, blocklistName applies to blocklist operations, and outputType is not part of the category- creation schema. Therefore, the correct payload fields to complete the cURL are definition and sampleBlobUrl.
Microsoft Azure AI References (titles only)
* Azure AI Content Safety - Create or update custom text categories (REST)
* Azure AI Content Safety - Custom categories concepts and training data (JSONL in blob storage)
* Azure AI Content Safety - Text analysis vs. category management endpoints

Azure AI Content Safety supports custom blocklists-dictionaries of terms/phrases you define to detect obscure or domain-specific offensive terms in user content. Creating a blocklist is the minimal-effort, built- in way to meet this requirement; you don't need to build a classifier.
References
* Create and use blocklists in Azure AI Content Safety.https://learn.microsoft.com/azure/ai-services
/content-safety/concepts/blocklists
* Text moderation overview (using built-in classifiers with optional blocklists).https://learn.microsoft.com
/azure/ai-services/content-safety/concepts/text-moderation

Explanation:
* Generate alt textTo automatically suggest descriptive captions for images (usable as alt text), use the Computer Vision Describe Image API. It returns natural-language captions summarizing the image content. Endpoint: /vision/v3.2/describe. Setting maxCandidates=1 gives a single best caption.
* Detect inappropriate contentTo block adult/racy/gory images with minimal effort, use Computer Vision Analyze Image with the Adult visual feature. This returns flags (isAdult, isRacy, isGory) and confidence scores. The provided option includes Adult,Description which still returns the needed adult
/racy/gore signals, satisfying the requirement.
These choices minimize development effort by using built-in Computer Vision capabilities without training a custom model or wiring up multiple services.
* Microsoft Learn - Describe images (Computer Vision): "The Describe Image API returns a list of natural language sentences that describe the image."https://learn.microsoft.com/azure/ai-services
/computer-vision/overview-image-analysis#describe-images
* Microsoft Learn - Analyze images (Adult/Racy/Gore detection): "Use the Adult feature to detect adult, racy, and gory content."https://learn.microsoft.com/azure/ai-services/computer-vision/overview-image- analysis#adult-racy-and-gory-content-detection

Explanation:

To make the chatbot respond only when the answer's confidence is # 95%, you must set the request body property confidenceScoreThreshold to 0.95 in the Query knowledge bases operation of Custom question answering. The REST API for querying a Custom question answering project is:
POST {Endpoint}/language/:query-knowledgebases?projectName={projectName}&deploymentName=
{deploymentName}&api-version=2021-10-01
Here, projectName identifies the Custom question answering project you're querying (the screenshot's placeholder <chatbot-project>), while deploymentName specifies which deployment (for example, production) to use. The request body includes confidenceScoreThreshold (0-1) to filter out answers below that score; setting it to 0.95 enforces the requirement.
Example snippet:
curl -X POST "$LANGUAGE_ENDPOINT/language/:query-knowledgebases?projectName=<chatbot- project>&deploymentName=production&api-version=2021-10-01" \
-H "Ocp-Apim-Subscription-Key: $LANGUAGE_KEY" \
-H "Content-Type: application/json" \
-d '{
"question": "How much energy does my phone have left?",
"confidenceScoreThreshold": 0.95
}'
References
* REST API: Question Answering - Get Answers (shows endpoint with projectName/deploymentName and the confidenceScoreThreshold request property). Microsoft Learn
* REST API (newer version) parameter list for projectName/deploymentName. Microsoft Learn