Kling AI Hello World
SkillMedia'Create your first Kling AI video generation with a minimal working example.
Use Kling AI Hello World in Claude, ChatGPT or Ahel Desktop
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Also: Claude Code · Cursor · Codex
Then ask your AI: use the Kling AI Hello World skill
Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by jeremylongshore/tons-of-skills-marketplace in skills/.curated/klingai-hello-world/SKILL.md and read by ahel’s review.
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-authsetup - Python 3.8+ with
requestsandPyJWT - 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
| Status | Meaning |
|---|---|
submitted | Task queued, waiting for processing |
processing | Video generation in progress |
succeed | Complete — video URL available |
failed | Generation failed — check task_status_msg |
Common First-Run Issues
| Problem | Fix |
|---|---|
401 response | JWT token expired or AK/SK wrong |
task_status: failed | Prompt too vague — add visual detail |
Empty videos array | Task still processing — poll longer |
| Slow generation | Standard mode takes 60-120s; use mode: "standard" for first test |
Cost
- 5-second standard video = 10 credits
- Free tier: 66 credits/day (refreshes daily, no rollover)
Instructions
- 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.
- Request one watermarked, draft-only canary and verify the task state, policy outcome, rights status, and destination before review.
- Cancel and remove the draft if quality, policy, attribution, or budget checks fail; do not publish from the smoke test.
- 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
| Condition | Response |
|---|---|
| Policy, rights, or attribution concern | Cancel the task, delete the draft, and route a redacted record for owner review. |
| Budget or task-state anomaly | Pause further submissions and restore the approved test configuration. |
Examples
env=sandbox; brief=synthetic-sky; mode=standard; duration=5s; policy=pass; destination=draft-only; cleanup=24h is an acceptable first canary.
Resources
Signals
- GitHub stars
- 3k
- Forks
- 415
- Last commit
- Oct 2026
Advanced
- Item type
- skill
- Key
klingai-hello-world- Source
- github.com/jeremylongshore/tons-of-skills-marketplace
github.com/jeremylongshore/tons-of-skills-marketplace
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