Building a Resilient, Multi-User Agentic Streaming Application (www.kitewing.ai)

A new architecture for building resilient, multi-user agentic streaming applications has been proposed, addressing common challenges faced when multiple users observe real-time AI agent processing. This architecture leverages a combination of Python and TypeScript, utilizing Server-Sent Events (SSE) for streaming while effectively managing state and user sessions through a database. The approach ensures robustness against issues like disconnections, server restarts, and multiple simultaneous viewers, transforming a direct data stream into a more manageable database polling operation. Significantly, the architecture defines Python as a stateless compute kernel, allowing for seamless integration with language-specific SDKs while moving UI and business logic to TypeScript, which offers a stronger type system and improved production capabilities. This clean separation prevents session state leakage, thereby minimizing bugs. The design employs a transformation stream for event handling, enabling persistent storage of streaming events and updates without compromising user experience. These enhancements not only streamline development but also enhance scalability and reliability, making this framework a valuable contribution to the AI/ML development community.