Imported from jeremylongshore/tons-of-skills-marketplace (skills/.curated/klingai-hello-world/SKILL.md). Install upstream with npx skills add jeremylongshore/tons-of-skills-marketplace --skill klingai-hello-world. Copyright stays with the author (MIT).

Kling AI Hello World

Overview

Generate your first AI video in under 20 lines of code. This skill walks through the complete create-poll-download cycle using the Kling AI REST API.

Base URL: https://api.klingai.com/v1

Prerequisites

• Completed klingai-install-auth setup
• Python 3.8+ with requests and PyJWT
• At least 10 credits in your Kling AI account

Minimal Example — Python

import jwt, time, os, requests

# --- Auth ---
def get_token():
    ak = os.environ["KLING_ACCESS_KEY"]
    sk = os.environ["KLING_SECRET_KEY"]
    payload = {"iss": ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5}
    return jwt.encode(payload, sk, algorithm="HS256",
                      headers={"alg": "HS256", "typ": "JWT"})

BASE = "https://api.klingai.com/v1"
HEADERS = {"Authorization": f"Bearer {get_token()}", "Content-Type": "application/json"}

# --- Step 1: Create task ---
task = requests.post(f"{BASE}/videos/text2video", headers=HEADERS, json={
    "model_name": "kling-v2-master",
    "prompt": "A golden retriever running through autumn leaves in slow motion, cinematic lighting",
    "duration": "5",
    "aspect_ratio": "16:9",
    "mode": "standard",
}).json()

task_id = task["data"]["task_id"]
print(f"Task created: {task_id}")

# --- Step 2: Poll until complete ---
import time as t
while True:
    t.sleep(10)
    status = requests.get(f"{BASE}/videos/text2video/{task_id}", headers=HEADERS).json()
    state = status["data"]["task_status"]
    print(f"Status: {state}")
    if state == "succeed":
        video_url = status["data"]["task_result"]["videos"][0]["url"]
        print(f"Video ready: {video_url}")
        break
    elif state == "failed":
        print(f"Failed: {status['data']['task_status_msg']}")
        break

Minimal Example — Node.js

import jwt from "jsonwebtoken";

const BASE = "https://api.klingai.com/v1";

function getHeaders() {
  const token = jwt.sign(
    { iss: process.env.KLING_ACCESS_KEY, exp: Math.floor(Date.now() / 1000) + 1800,
      nbf: Math.floor(Date.now() / 1000) - 5 },
    process.env.KLING_SECRET_KEY,
    { algorithm: "HS256", header: { typ: "JWT" } }
  );
  return { Authorization: `Bearer ${token}`, "Content-Type": "application/json" };
}

// Create task
const res = await fetch(`${BASE}/videos/text2video`, {
  method: "POST",
  headers: getHeaders(),
  body: JSON.stringify({
    model_name: "kling-v2-master",
    prompt: "A golden retriever running through autumn leaves in slow motion",
    duration: "5",
    aspect_ratio: "16:9",
    mode: "standard",
  }),
});
const { data } = await res.json();
console.log(`Task: ${data.task_id}`);

// Poll
const poll = setInterval(async () => {
  const r = await fetch(`${BASE}/videos/text2video/${data.task_id}`, { headers: getHeaders() });
  const s = await r.json();
  if (s.data.task_status === "succeed") {
    console.log("Video:", s.data.task_result.videos[0].url);
    clearInterval(poll);
  } else if (s.data.task_status === "failed") {
    console.error("Failed:", s.data.task_status_msg);
    clearInterval(poll);
  }
}, 10000);

Response Shape

{
  "code": 0,
  "message": "success",
  "data": {
    "task_id": "abc123...",
    "task_status": "succeed",
    "task_result": {
      "videos": [{
        "id": "vid_001",
        "url": "https://cdn.klingai.com/...",
        "duration": "5.0"
      }]
    }
  }
}

Task Status Values

Common First-Run Issues

Cost

• 5-second standard video = 10 credits
• Free tier: 66 credits/day (refreshes daily, no rollover)

Instructions

1. Run the first request in a sandbox using a synthetic or rights-cleared brief and an approved credit cap; never paste credentials into code or logs.
2. Request one watermarked, draft-only canary and verify the task state, policy outcome, rights status, and destination before review.
3. Cancel and remove the draft if quality, policy, attribution, or budget checks fail; do not publish from the smoke test.
4. Record only a redacted receipt and delete temporary assets at the approved retention boundary.

Output

Produce a first-render receipt with environment, brief classification, model/mode, duration, credit estimate, task state, policy/rights checks, draft-only assertion, owner, and cleanup reference. Exclude prompts, asset URLs, identities, and secrets.

Error Handling

Examples

env=sandbox; brief=synthetic-sky; mode=standard; duration=5s; policy=pass; destination=draft-only; cleanup=24h is an acceptable first canary.

Resources

• Kling AI Text-to-Video API
• Developer Portal