Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are creating a custom question answering project in Azure AI Language. The FAQ must respond in either English or Spanish, depending on the language of the user's query. The knowledge base content for each language is already available. According to Azure AI Language design recommendations, which approach should you implement to build a maintainable multi-language solution?
Create a single project, import both English and Spanish knowledge sources, and rely on the service to auto-detect language at query time.
Create an English project and a Spanish project, then have the client detect the query language and call the corresponding project endpoint.
Create one English project and configure a custom Translator model so Spanish questions are translated to English before they are sent to the project.
Create one project in English, enable cross-language semantic search, and return the same answers for Spanish queries.
A custom question answering project is always linked to a single language locale. To provide answers in more than one language, you create a separate project for each language (for example, one project with locale en-us and another with locale es-es). At run time your client application detects the user's language or inspects the Accept-Language header, then routes the request to the endpoint of the matching project. Adding multiple languages to one project, translating queries on the fly, or relying on cross-language embedding are not supported ways to build a production multi-language knowledge base in Azure AI Language.
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Microsoft Azure AI Engineer Associate AI-102
Implement natural language processing solutions
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