Migrating to a Multimodal AI Framework: A Step-by-Step Guide for C# Developers

The author transitioned from traditional to multimodal AI in C# due to a chatbot's inability to analyze images in support tickets. Multimodal AI processes multiple data types like text and images, offering richer context than single-modality approaches, improving diagnostic accuracy. The migration involved auditing existing AI implementations, selecting a framework (LlmTornado was chosen for its native multimodal support and provider flexibility), and installing necessary packages. The author then migrated text-plus-image workflows, using the `ChatMessagePart` to combine inputs, and incorporated audio capabilities by transcribing audio memos. PDF document processing was also streamlined, improving contract analysis. Streaming was implemented for efficiency, improving user experience. The author addressed error handling with fallback strategies for file size limits and model capability checks. Finally, the author highlighted the importance of monitoring costs and performance throughout the process.