A technical guide for adding AI capabilities (chat, vision, voice) to Flutter apps. Strategies for lazy loading, response streaming, and state management for a smooth UX.
Integrating generative AI into Flutter apps requires careful architectural decisions to avoid compromising user experience. For streaming chat, we recommend the dart_openai package with StreamBuilder, which allows displaying tokens in real time without blocking the main thread. For computer vision (image analysis), processing should be done on the FastAPI backend and only the result returned to the client.
For voice synthesis, ElevenLabs offers a Flutter-compatible SDK that enables streaming playback. The state patterns that work best are Riverpod for managing asynchronous calls and loading states. The biggest challenge is bundle size: never include ML models directly in the app, always point to an API.
With these practices, we have built apps with full AI capabilities that weigh less than 15MB and have perceived response times under 300ms.