klingai-async-workflows

name	klingai-async-workflows
description	Build async video generation workflows with Kling AI using queues, state machines, and event-driven patterns. Trigger with phrases like 'klingai async', 'kling ai workflow', 'klingai pipeline', 'async video generation'.
allowed-tools	Read, Write, Edit, Bash(npm:*), Grep
version	1.18.0
license	MIT
author	Jeremy Longshore <[e-mail]>
tags	["saas","kling-ai","async","workflows"]
compatibility	Designed for Claude Code, also compatible with Codex and OpenClaw

Kling AI Async Workflows

Overview

Kling AI video generation is inherently async: you submit a task, then poll or receive a callback when done. This skill covers production patterns for integrating this into larger systems using queues, state machines, and event-driven architectures.

Core Pattern: Submit + Callback

import jwt, time, os, requests

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

def get_headers():
    ak, sk = os.environ["KLING_ACCESS_KEY"], os.environ["KLING_SECRET_KEY"]
    token = jwt.encode(
        {"iss": ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5},
        sk, algorithm="HS256", headers={"alg": "HS256", "typ": "JWT"}
    )
    return {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}

def submit_async(prompt, callback_url=None, **kwargs):
    """Submit task and return immediately."""
    body = {
        "model_name": kwargs.get("model", "kling-v2-master"),
        "prompt": prompt,
        "duration": str(kwargs.get("duration", 5)),
        "mode": kwargs.get("mode", "standard"),
    }
    if callback_url:
        body["callback_url"] = callback_url

    r = requests.post(, headers=get_headers(), json=body)
     r.json()[][]