Microsoft Azure AI Engineer Associate AI-102 Practice Question
Your internal support tool must run this workflow: classify messages with GPT-3.5-turbo, branch to a fine-tuned GPT-4 reply generator only when the classifier's confidence ≥ 0.7, and expose the whole process as a single HTTPS endpoint that you can later containerize for Azure Container Apps with step-level tracing. Which Azure capability lets you orchestrate this multi-model flow with minimal custom code?
Create a prompt flow in Azure AI Studio (or Azure AI Foundry) and deploy the flow as a managed endpoint.
Publish both model endpoints to Azure Event Grid and use event subscriptions with advanced filters to control routing.
Build the workflow in Azure Logic Apps Standard using the Azure OpenAI connector for both model calls.
Implement the pattern with an Azure Durable Function that uses fan-out/fan-in orchestration between two HTTP-triggered functions.
Prompt flow (available in Azure AI Studio and Azure AI Foundry) is specifically designed to orchestrate multi-step generative AI workflows. A flow allows you to chain several LLM calls, add conditional logic such as branching on a confidence score, capture detailed telemetry for each step, and publish the entire pipeline as a REST endpoint or container image that can be run in Azure Container Apps or other environments. Logic Apps and Durable Functions can call LLM endpoints but do not offer built-in prompt management, token-level tracing, or automatic packaging of the complete LLM workflow. Event Grid provides event routing, not workflow orchestration for models.
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