Kling O1 Video 2 Video Reference 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": "Based on @Video1, generate the next shot. Keep the style of the video man drives fast and fall on the road",
11    "video_url": "https://segmind-inference-inputs.s3.amazonaws.com/2c499e1e-2b40-4833-b9dd-37a47f8e52e6-seedance_1.5_output.mp4",
12    "image_urls": ["https://segmind-inference-inputs.s3.amazonaws.com/bacc9f7c-6375-4138-9695-d4654f59d78a-output-1767722935251.png", "https://segmind-inference-inputs.s3.amazonaws.com/bf576f0d-58e5-4234-9431-523d34df184e-output-1767723467082.png"],
13    "aspect_ratio": "auto",
14    "duration": "5",
15    "keep_audio": False,
16}
17job = client.submit_async("kling-o1-video-to-video-reference", **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-o1-video-to-video-reference", **payload)