Seedream 5.0 Pro Layer Decomposition Serverless API

 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3import segmind
 4
 5# Async (v2): submit to the queue and block until COMPLETED.
 6# run() returns the final result dict (600s deadline, 1.0s poll by default).
 7result = segmind.run(
 8    "seedream-5-pro-layer-decomposition",
 9    image="https://segmind-resources.s3.amazonaws.com/input/seedream-5-pro-layer-decomposition-input.jpeg",
10    prompt="Separate three layers: the orange coffee mug, the green potted succulent, and the stack of books.",
11    size="2K",
12    output_format="png",
13    optimize_prompt_mode="standard",
14    watermark=False,
15)
16print(result["status"])                      # COMPLETED
17print(result.get("output"))                  # model output (e.g. media URL)
18print(result["metrics"]["inference_time"])   # server compute seconds
19
20# --- Or submit + poll manually (track request_id, control the cadence) ---
21from segmind import SegmindClient, InferenceFailed, InferenceTimeout
22
23client = SegmindClient()                      # reads SEGMIND_API_KEY
24payload = {
25    "image": "https://segmind-resources.s3.amazonaws.com/input/seedream-5-pro-layer-decomposition-input.jpeg",
26    "prompt": "Separate three layers: the orange coffee mug, the green potted succulent, and the stack of books.",
27    "size": "2K",
28    "output_format": "png",
29    "optimize_prompt_mode": "standard",
30    "watermark": False,
31}
32job = client.submit_async("seedream-5-pro-layer-decomposition", **payload)
33print(job.request_id)                         # available immediately
34try:
35    result = job.wait(timeout=600, interval=1.0)
36except InferenceTimeout as e:
37    print("still running:", e.request_id)
38except InferenceFailed as e:
39    print("failed:", e.detail)