Kling Avatar V2 Standard 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/74bce37e-151d-4923-a56f-b5f9ce6e5134-601140c8-73e5-4490-8911-e6c7d3dc0e70-infinite_talk_ip.webp",
11    "audio_url": "https://segmind-resources.s3.amazonaws.com/input/ce1dcce7-c5b1-4cf6-a42f-65bed682a44a-news-reading-small.mp3",
12    "prompt": "news reporter speaking",
13}
14job = client.submit_async("kling-v2-standard-avatar", **payload)
15print(job.request_id)                         # available immediately
16try:
17    result = job.wait(timeout=900, interval=2.0)
18    print(result["status"])                  # COMPLETED
19    print(result.get("output"))              # model output (e.g. video URL)
20except InferenceTimeout as e:
21    print("still running:", e.request_id)    # re-poll later with this id
22except InferenceFailed as e:
23    print("failed:", e.detail)
24
25# Fast models (<=600s) can use the one-liner instead:
26# result = segmind.run("kling-v2-standard-avatar", **payload)