klingai-batch-processing

# Kling AI Batch Processing ## Overview Generate multiple videos efficiently using controlled parallelism, rate-limit-aware submission, progress tracking, and result collection. All requests go through `https://api.klingai.com/v1`. ## Batch Submission with Rate Limiting ```python 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_batch(prompts, model="kling-v2-master", duration="5", mode="standard", max_concurrent=3, delay=2.0): """Submit batch with controlled concurrency and pacing.""" tasks = [] active = [] for i, prompt in enumerate(prompts): # Wait if at concurrency limit while len(active) >= max_concurrent: active = [t for t in active if not check_complete(t["task_id"])] if len(active) >= max_concurrent: time.sleep(5) response = requests.post(f"{BASE}/videos/text2video", headers=get_headers(), json={ "model_name": model, "prompt": prompt, "duration": duration, "mode": mode, }) data = response.json()["data"] task = {...