Multi-modal Content Support

The User Problem This Pattern Solves

Text is often an inefficient and incomplete medium for explaining visual or spatial concepts. A user asking, "How does the A-742 engine's compressor work?" or "Show me the network topology for the London data center" would be poorly served by a text-only response. This forces the user to perform a second search for images or diagrams, creating friction and leading to a fragmented understanding.

The Design Solution & UI Mockup

The solution is a multi-modal AI that can intelligently determine when a visual aid is the most effective way to answer a query. The interface is designed to seamlessly integrate images into a conversational flow. When the user asks a technical question, the AI provides a concise text summary accompanied by a high-quality, relevant diagram. This allows the user to read the explanation and see the schematic simultaneously, providing a rich, complete, and highly efficient learning experience.

Explain the compressor stage of the A-742 engine.

The A-742 engine features a 3-stage fan and a 6-stage high-pressure compressor. Air is drawn in by the fan, compressed, and then forced into the high-pressure compressor, significantly increasing its pressure and temperature before it enters the combustor.

Fig. 1: Cross-section of the A-742 compressor and fan stages.

Key Benefits & Impact

Design Considerations

The key challenge is relevance—the AI must retrieve the correct visual for the context. The system needs a robust way to associate images and diagrams with specific concepts and entities in its knowledge base. The UI must also be responsive, ensuring that images are displayed correctly on all screen sizes. For professional use, providing a source for the image (e.g., "Source: A-742 Technical Manual, pg. 87") is critical for user trust and verification.