Stop Making Your AI Chatbot Slower: Streaming Responses with Spring AI and Server-Sent Events

Spring AI's streaming support combined with Server-Sent Events (SSE) reduces perceived response time for AI chatbots from 8 seconds to 200-500 milliseconds for the first token. The approach, demonstrated with a Spring Boot controller and JavaScript EventSource integration, streams tokens to the browser as they are generated rather than waiting for the full response. This architecture improves user experience by showing immediate progress, reducing bounce rates even when total generation time remains unchanged.

The Wrong Approach Most applications follow this flow: User Query ↓ LLM Request ↓ Wait 5-10 Seconds ↓ Return Full Response The Better Architecture Use Spring AI's streaming support combined with Server-Sent Events SSE . User Query ↓ Spring AI ↓ Streaming Tokens ↓ SSE Endpoint ↓ Browser Updates UI Instantly Spring AI Streaming Example @RestController @RequiredArgsConstructor public class ChatController { private final ChatClient chatClient; @GetMapping value = "/chat/stream", produces = MediaType.TEXT EVENT STREAM VALUE public Flux<String streamResponse @RequestParam String message { return chatClient.prompt .user message .stream .content ; } } Frontend Integration js const eventSource = new EventSource "/chat/stream?message=Explain Spring AI" ; eventSource.onmessage = event = { document.getElementById "output" .innerHTML += event.data; }; Performance Benefits Faster Perceived Response Time Even if the model takes 8 seconds to complete: Without Streaming → First token after 8s With Streaming → First token after 200-500ms The total generation time remains the same, but users perceive the application as significantly faster. Reduced Bounce Rate Users are less likely to leave while waiting because they can see progress immediately. Better AI UX Streaming makes even local Ollama models feel responsive.