Luma Ray 3.2 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": "The woman's flowing red dress and long hair billow dramatically in the strong sea breeze, turquoise ocean waves surge and crash into white foam against the rocks below, seabirds glide gracefully across the glowing golden-hour sky, soft clouds drift slowly, gentle cinematic camera push-in, smooth fluid natural motion, photorealistic, ultra detailed",
11    "start_frame": "https://segmind-resources.s3.amazonaws.com/input/luma-ray-3-2-img-2-video-start-frame.jpg",
12    "resolution": "720p",
13    "duration": "5s",
14    "aspect_ratio": "16:9",
15}
16job = client.submit_async("luma-ray-3-2", **payload)
17print(job.request_id)                         # available immediately
18try:
19    result = job.wait(timeout=900, interval=2.0)
20    print(result["status"])                  # COMPLETED
21    print(result.get("output"))              # model output (e.g. video URL)
22except InferenceTimeout as e:
23    print("still running:", e.request_id)    # re-poll later with this id
24except InferenceFailed as e:
25    print("failed:", e.detail)
26
27# Fast models (<=600s) can use the one-liner instead:
28# result = segmind.run("luma-ray-3-2", **payload)