Building Real-Time RAG with Websockets and PHP
Delivering streaming LLM responses directly to web pages creates a highly reactive conversational user interface. In traditional setups, HTTP polling leads to high latency. By leveraging **Websockets** alongside PHP server daemons, we can stream real-time Retrieval-Augmented Generation outputs efficiently.
WebSocket Server Architecture
We configure a PHP Ratchet server that listens for user connections, Queries the Vector database, and streams OpenAI chunks back to the client token-by-token.
// Client-side socket listener
const socket = new WebSocket("ws://localhost:8080/rag");
socket.onmessage = (event) => {
const payload = JSON.parse(event.data);
document.getElementById("output").innerText += payload.token;
};
Key Benefits
WebSocket connections avoid header overhead on repeated requests, reducing TTFB (Time to First Token) to less than 100 milliseconds and providing a glassy, smooth typing effect for developers.