klingai-hello-world

Create your first Kling AI video generation with a minimal working example. Use when learning Kling AI or testing your setup. Trigger with phrases like 'kling ai hello world', 'first kling video', 'klingai quickstart', 'test klingai'.

1,868 stars

Best use case

klingai-hello-world is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Create your first Kling AI video generation with a minimal working example. Use when learning Kling AI or testing your setup. Trigger with phrases like 'kling ai hello world', 'first kling video', 'klingai quickstart', 'test klingai'.

Teams using klingai-hello-world should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/klingai-hello-world/SKILL.md --create-dirs "https://raw.githubusercontent.com/jeremylongshore/claude-code-plugins-plus-skills/main/plugins/saas-packs/klingai-pack/skills/klingai-hello-world/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/klingai-hello-world/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How klingai-hello-world Compares

Feature / Agentklingai-hello-worldStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Create your first Kling AI video generation with a minimal working example. Use when learning Kling AI or testing your setup. Trigger with phrases like 'kling ai hello world', 'first kling video', 'klingai quickstart', 'test klingai'.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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

```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

```javascript
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

```json
{
  "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)

## Resources

- [Kling AI Text-to-Video API](https://app.klingai.com/global/dev/document-api/apiReference/model/textToVideo)
- [Developer Portal](https://app.klingai.com/global/dev)

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