ULTRA-FAST SCRAPER NODE

Spawn AI Node

Akses engine pemrosesan data real-time dengan integrasi Deep Thinking. Dioptimalkan secara sempurna untuk parsing data terstruktur dengan hasil langsung dalam format JSON. Endpoints tersedia via GET dan POST.

GET/POST

https://stenly.org/api/spawn-ai

Live

Header & Payload Schema

Parameter	Type	Description
prompt/q*	String	Input teks instruksi operasional untuk engine AI. Dapat menggunakan key prompt, message, atau q.
think	Boolean	Mode reasoning untuk hybrid chain-of-thought (CoT). Jika true akan menyertakan log aktivitas pemikiran.

Full Integration Guide

Siapkan Request REST

Lakukan request ke endpoint kami menggunakan metode POST/GET. Pastikan parameter URL atau Body JSON kamu sudah sesuai.

Terminal / Bash (cURL - GET)

curl "https://stenly.org/api/spawn-ai?q=System+metrics&think=true"

Terminal / Bash (cURL - POST)

curl -X POST "https://stenly.org/api/spawn-ai" \
-H "Content-Type: application/json" \
-d '{"prompt":"System metrics...","think":true}'

Python (Requests)

import requests

url = "https://stenly.org/api/spawn-ai"
res = requests.post(url, json={ "prompt": "System metrics...", "think": True })
print(res.json())

Node.js (Fetch)

const res = await fetch("https://stenly.org/api/spawn-ai", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({ prompt: "System metrics...", think: true })
});
const data = await res.json();

Hasil Yang Didapatkan (Response)

HTTP Headers

HTTP/1.1 200 OK

Content-Type: application/json

X-Stenly-Engine: Spawn-V2-Node

X-Status: Stable_OK

Stream / Payload Output

{
"status": true,
"author": "STENLY",
"creator": "STENLY",
"result": {
"question": "System metrics...",
"answer": "Modular processing completed...",
"think_mode": true,
"thinking_process": "[searching]...",
"model": "spawnai",
"session_id": "s_12345..."
}
}

tty1

# SYSDIN REQUEST

Research AI capabilities for automation

# RAW SCHEMA

{
  "prompt": "Research AI capabilities for automation",
  "think": true
}

REASONING