Seedance 1.0 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    "image_url": "https://segmind-resources.s3.amazonaws.com/input/1a5d8acb-e087-4cd9-875f-aad0d6c7e7a5-horse_track.png",
11    "duration": 5,
12    "prompt": "A powerful chestnut horse gallops fiercely along a muddy racetrack. [Low-angle shot] Captures several horses with jockeys racing neck and neck, mud spraying from their hooves in the rain. [Overhead shot] The camera slowly pulls upward, revealing the full track curving through a packed stadium under overcast skies.",
13    "resolution": "720p",
14    "seed": 12345,
15    "camera_fixed": False,
16    "aspect_ratio": "16:9",
17    "skip_moderation": "false",
18}
19job = client.submit_async("seedance-pro", **payload)
20print(job.request_id)                         # available immediately
21try:
22    result = job.wait(timeout=900, interval=2.0)
23    print(result["status"])                  # COMPLETED
24    print(result.get("output"))              # model output (e.g. video URL)
25except InferenceTimeout as e:
26    print("still running:", e.request_id)    # re-poll later with this id
27except InferenceFailed as e:
28    print("failed:", e.detail)
29
30# Fast models (<=600s) can use the one-liner instead:
31# result = segmind.run("seedance-pro", **payload)