Seedance 1.5 Pro 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    "first_frame_url": "https://segmind-resources.s3.amazonaws.com/input/2398ce6d-ab67-4c6f-9ef6-144d64fd7b34-first_frame.jpg",
11    "duration": 5,
12    "prompt": "A sleek black Porsche 911 on a coastal cliff road at golden hour - camera slowly orbits 90 degrees around the car revealing the vast ocean backdrop - cinematic smooth orbital camera movement - warm golden backlit glow with lens flares - engine ignition roar fading into crashing ocean waves and coastal wind",
13    "resolution": "720p",
14    "seed": 12345,
15    "camera_fixed": False,
16    "aspect_ratio": "16:9",
17    "generate_audio": True,
18    "skip_moderation": "false",
19}
20job = client.submit_async("seedance-1.5-pro", **payload)
21print(job.request_id)                         # available immediately
22try:
23    result = job.wait(timeout=900, interval=2.0)
24    print(result["status"])                  # COMPLETED
25    print(result.get("output"))              # model output (e.g. video URL)
26except InferenceTimeout as e:
27    print("still running:", e.request_id)    # re-poll later with this id
28except InferenceFailed as e:
29    print("failed:", e.detail)
30
31# Fast models (<=600s) can use the one-liner instead:
32# result = segmind.run("seedance-1.5-pro", **payload)