Streaming AI Responses in Real-Time with SSE in Next.js & NestJS

Are long AI wait times hurting your app? Learn how Server-Sent Events deliver responses in under 200 milliseconds, boosting retention and cutting costs.

#1about 4 minutes

Why streaming AI responses improves user experience

Streaming AI text token-by-token significantly improves user retention and engagement compared to showing a loading screen.

#2about 2 minutes

Comparing SSE, WebSockets, and polling for real-time data

Server-Sent Events (SSE) offer a lightweight, unidirectional alternative to WebSockets for pushing data, consuming half the memory per connection.

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A full-stack architecture for streaming AI responses

The frontend uses the browser's EventSource API to subscribe to a NestJS backend endpoint that streams data from an AI provider.

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Implementing an SSE endpoint in NestJS for AI streaming

Set the `text/event-stream` content type and use a loop to push data chunks received from the OpenAI or Gemini streaming API to the client.

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Consuming SSE streams in Next.js with EventSource

Use the native `EventSource` object to connect to the streaming endpoint and append incoming data to the component's state for a typewriter effect.

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Using SSE for notifications and real-time file sharing

A code demonstration shows how to manage multiple client connections and push different event types, such as notifications or file data, to all subscribers.

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Preparing an SSE implementation for production environments

Ensure reliability in production by adding authentication guards, rate limiting, keep-alive messages, and configuring proxy buffering in Nginx.

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Scaling SSE applications for thousands of concurrent users

For large-scale applications, progress from a simple load balancer to using Redis Streams for message queuing or a dedicated SSE hub infrastructure.

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Comparing AI providers for optimal streaming performance

AI providers like Groq, Gemini, and OpenAI differ in their streaming approach, offering either token-by-token or chunk-by-chunk responses which impacts perceived speed.

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Syncing data from ChatGPT to multiple client applications

A custom GPT action can trigger a backend process that uses SSE to push new data in real-time to a user's browser extension, desktop, and mobile apps simultaneously.

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Understanding SSE limitations and its key benefits

Use SSE for unidirectional server-to-client data push, but choose other protocols like WebRTC for video or gRPC for microservices, to leverage its benefits of low latency and better user trust.