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config-websockets/streaming/server (OpenAI WebSocket Server)
Simple Node.js server using Express and native WebSockets that exposes two real-time endpoints to interact with the OpenAI Responses API.
Requirements
- Node.js >= 18.17
- An OpenAI API key
Setup
- Install dependencies:
npm install
- Configure environment:
- set
OPENAI_API_KEYin your environment or use .env file
cp env.example .env
# edit .env and set OPENAI_API_KEY
- Start the server (defaults to port 3300):
npm start
You can also run in dev mode with automatic restarts:
npm run dev
HTTP
- Health check:
GET /health→{ "status": "ok" }
Real-time (WebSocket)
Two WebSocket upgrade paths are provided:
/ws— non-streaming. Emits a singleresponsewhen the OpenAI request completes./ws-stream— streaming. Emits incrementaldeltaandmessageevents, thendone.
Both endpoints accept the same request payload (model is configured via env):
{ "input": "Hello there!" }
Model is read from CHATBOT_MODEL env var and defaults to gpt-4.1-mini.
Client examples
Non-streaming (/ws):
const ws = new WebSocket('ws://localhost:3300/ws');
ws.onopen = () => {
ws.send(JSON.stringify({ input: 'Hello there!' }));
};
ws.onmessage = (event) => {
const msg = JSON.parse(event.data);
// msg.type: 'ready' | 'response' | 'done' | 'error'
console.log(msg);
};
ws.onerror = (err) => console.error('ws error', err);
Streaming (/ws-stream):
const ws = new WebSocket('ws://localhost:3300/ws-stream');
ws.onopen = () => {
ws.send(JSON.stringify({ input: 'Stream this please' }));
};
ws.onmessage = (event) => {
const msg = JSON.parse(event.data);
// msg.type: 'ready' | 'delta' | 'message' | 'done' | 'error'
if (msg.type === 'delta') process.stdout.write(msg.message || '');
else console.log(msg);
};
ws.onerror = (err) => console.error('ws error', err);
Notes
- Configure port via
PORTin.env. - Configure model via
CHATBOT_MODELin.env(default:gpt-4.1-mini). - Health route is
GET /health. WebSocket upgrade paths are/wsand/ws-stream.