Kling 2.5 Turbo Serverless API

 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3from segmind import SegmindClient, InferenceFailed, InferenceTimeout
 4
 5# Async (v2) — recommended for long-running / video models.
 6# run() blocks up to 600s; submit_async + job.wait(timeout=...) sets a longer
 7# deadline and keeps the request_id so you can re-poll later.
 8client = SegmindClient()                      # reads SEGMIND_API_KEY
 9payload = {
10    "prompt": "A beloved community figure moves through a 1920s street carnival, warmly interacting with attendees. Vintage cars, dancing performers, and striped carnival tents fill the scene. Camera follows closely in a handheld cinematic style, capturing intimate smiles and connections, shallow depth of field, 4K UHD, golden warm lighting.",
11    "negative_prompt": "no dark tones, no blur, no distort",
12    "cfg_scale": 0.7,
13    "duration": "10",
14    "mode": "pro",
15    "aspect_ratio": "16:9",
16}
17job = client.submit_async("kling-2.5-turbo", **payload)
18print(job.request_id)                         # available immediately
19try:
20    result = job.wait(timeout=900, interval=2.0)
21    print(result["status"])                  # COMPLETED
22    print(result.get("output"))              # model output (e.g. video URL)
23except InferenceTimeout as e:
24    print("still running:", e.request_id)    # re-poll later with this id
25except InferenceFailed as e:
26    print("failed:", e.detail)
27
28# Fast models (<=600s) can use the one-liner instead:
29# result = segmind.run("kling-2.5-turbo", **payload)