GPT Image 1 Edit Mini 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    "gpt-image-1-edit-mini",
 9    prompt="Use the reference airship scene. Make it larger scale and more dynamic, with multiple airships in the sky, steam trails, moving propellers, and adventurous characters posing heroically. Retain steampunk details and style.",
10    image_urls=["https://segmind-resources.s3.amazonaws.com/input/be87b383-38d7-435e-a795-5ece083301e9-0f4a926b22d2b98cf40bf1e17385deed_0.jpeg"],
11    mask=None,
12    size="auto",
13    quality="auto",
14    background="opaque",
15    output_compression=100,
16    output_format="png",
17    moderation="auto",
18)
19print(result["status"])                      # COMPLETED
20print(result.get("output"))                  # model output (e.g. media URL)
21print(result["metrics"]["inference_time"])   # server compute seconds
22
23# --- Or submit + poll manually (track request_id, control the cadence) ---
24from segmind import SegmindClient, InferenceFailed, InferenceTimeout
25
26client = SegmindClient()                      # reads SEGMIND_API_KEY
27payload = {
28    "prompt": "Use the reference airship scene. Make it larger scale and more dynamic, with multiple airships in the sky, steam trails, moving propellers, and adventurous characters posing heroically. Retain steampunk details and style.",
29    "image_urls": ["https://segmind-resources.s3.amazonaws.com/input/be87b383-38d7-435e-a795-5ece083301e9-0f4a926b22d2b98cf40bf1e17385deed_0.jpeg"],
30    "mask": None,
31    "size": "auto",
32    "quality": "auto",
33    "background": "opaque",
34    "output_compression": 100,
35    "output_format": "png",
36    "moderation": "auto",
37}
38job = client.submit_async("gpt-image-1-edit-mini", **payload)
39print(job.request_id)                         # available immediately
40try:
41    result = job.wait(timeout=600, interval=1.0)
42except InferenceTimeout as e:
43    print("still running:", e.request_id)
44except InferenceFailed as e:
45    print("failed:", e.detail)