Microsoft Azure AI Engineer Associate AI-102 Practice Question
You create a custom question answering project in Azure Language Studio by importing a product FAQ. After adding follow-up prompts and selecting Save and Train, training succeeds. Your developers query the knowledge base through the public REST runtime endpoint, but they receive HTTP 404 Not Found. What should you do in Language Studio to resolve the issue?
Regenerate the authoring and prediction keys of the Language resource and update the application.
Publish the project to the Production deployment environment.
Export the project as a .json file, delete the original project, and reimport the file into a new Language resource.
Enable WebSockets in the App Service that hosts the web application.
Save and Train only creates or updates the authoring version of the project. For the runtime REST endpoint to return answers, the project must be published to a deployment slot (Staging or Production). Publishing creates the prediction index that the public endpoint queries. Regenerating keys, enabling WebSockets, or re-importing the project will not make the knowledge base available until it has been published.
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Microsoft Azure AI Engineer Associate AI-102
Implement natural language processing solutions
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