Build a real-time streaming AI chatbot with zero streaming infrastructure - async + webhooks + failover

This text describes a full-stack example for building a production-ready AI chatbot using ModelRiver. It aims to demonstrate how to achieve true end-to-end streaming with async requests and event-driven webhooks. The architecture involves a React frontend, a Node.js backend, ModelRiver, and real-time WebSocket communication. ModelRiver acts as an AI gateway, handling streaming, failover, and structured outputs. The backend receives user messages and sends them to ModelRiver. ModelRiver processes the request and sends a webhook to the backend for enrichment. After enrichment, the backend calls back to ModelRiver, which streams the response to the frontend. The setup requires a ModelRiver account, Node.js, and a React frontend. The backend handles the chat request, webhook processing, and callback to ModelRiver. The frontend uses the ModelRiver client SDK to connect and stream responses. The demo allows for local development without the need for tools like ngrok. The benefits include instant streaming, reliability, structured outputs, business logic integration, and no heavy infrastructure. The tutorial provides a full code repository and documentation for further exploration.