Question

Your team is building a customer-support agent in Azure AI Foundry that must accept photos of damaged products uploaded by customers and generate a written triage summary describing the visible defects. You need to deploy a model into your Foundry project and expose it to the agent so it can process both the image and an accompanying text description in a single request. Which approach correctly enables this capability?

Accepted Answer

Deploy a multimodal (vision-capable) model such as GPT-4o to a project deployment, then have the agent send messages that include both image and text content parts.

Answer

Deploy a text-only chat model and pre-process each image with an OCR connector, passing only the extracted text to the model.

Answer

Deploy an embeddings model and use it to convert the image into a vector that the agent forwards to the chat completion endpoint.

Answer

Deploy a small language model (SLM) at the edge because it natively handles image inputs with the lowest latency.