Seedream 5.0 Pro 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",
 9    prompt="A hyper-detailed macro photograph of a hummingbird hovering beside a dew-covered red hibiscus flower at sunrise, iridescent emerald and sapphire feathers catching warm golden light, tiny water droplets sparkling, soft creamy bokeh background, ultra sharp focus, professional wildlife photography",
10    image_input=[],
11    aspect_ratio="3:2",
12    size="2K",
13    output_format="jpeg",
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    "prompt": "A hyper-detailed macro photograph of a hummingbird hovering beside a dew-covered red hibiscus flower at sunrise, iridescent emerald and sapphire feathers catching warm golden light, tiny water droplets sparkling, soft creamy bokeh background, ultra sharp focus, professional wildlife photography",
26    "image_input": [],
27    "aspect_ratio": "3:2",
28    "size": "2K",
29    "output_format": "jpeg",
30    "watermark": False,
31}
32job = client.submit_async("seedream-5-pro", **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)