SeedEdit 3.0 i2i 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    "seededit-v3",
 9    prompt="Replace the background with a sunny beach scene, keep lighting consistent.",
10    image_url="https://segmind-resources.s3.amazonaws.com/input/310c635e-98ec-413e-90bd-a3958c0f94ce-03e6053a-24ed-4466-84b7-a0878e211fc0.jpeg",
11    size="adaptive",
12    seed=42,
13    guidance_scale=5.5,
14)
15print(result["status"])                      # COMPLETED
16print(result.get("output"))                  # model output (e.g. media URL)
17print(result["metrics"]["inference_time"])   # server compute seconds
18
19# --- Or submit + poll manually (track request_id, control the cadence) ---
20from segmind import SegmindClient, InferenceFailed, InferenceTimeout
21
22client = SegmindClient()                      # reads SEGMIND_API_KEY
23payload = {
24    "prompt": "Replace the background with a sunny beach scene, keep lighting consistent.",
25    "image_url": "https://segmind-resources.s3.amazonaws.com/input/310c635e-98ec-413e-90bd-a3958c0f94ce-03e6053a-24ed-4466-84b7-a0878e211fc0.jpeg",
26    "size": "adaptive",
27    "seed": 42,
28    "guidance_scale": 5.5,
29}
30job = client.submit_async("seededit-v3", **payload)
31print(job.request_id)                         # available immediately
32try:
33    result = job.wait(timeout=600, interval=1.0)
34except InferenceTimeout as e:
35    print("still running:", e.request_id)
36except InferenceFailed as e:
37    print("failed:", e.detail)