GPT Image 1 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-mini",
 9    prompt="Design a pop-art urban street-inspired cover. Bright yellow, red, cyan with black/white contrast. Include graffiti textures, comic-style murals, playful stickers, and hand-drawn typography. Bold, energetic, and vibrant style, ideal for street festivals, concerts, or city cultural events.",
10    size="1024x1024",
11    quality="high",
12    moderation="auto",
13    background="opaque",
14    output_compression=100,
15    output_format="png",
16)
17print(result["status"])                      # COMPLETED
18print(result.get("output"))                  # model output (e.g. media URL)
19print(result["metrics"]["inference_time"])   # server compute seconds
20
21# --- Or submit + poll manually (track request_id, control the cadence) ---
22from segmind import SegmindClient, InferenceFailed, InferenceTimeout
23
24client = SegmindClient()                      # reads SEGMIND_API_KEY
25payload = {
26    "prompt": "Design a pop-art urban street-inspired cover. Bright yellow, red, cyan with black/white contrast. Include graffiti textures, comic-style murals, playful stickers, and hand-drawn typography. Bold, energetic, and vibrant style, ideal for street festivals, concerts, or city cultural events.",
27    "size": "1024x1024",
28    "quality": "high",
29    "moderation": "auto",
30    "background": "opaque",
31    "output_compression": 100,
32    "output_format": "png",
33}
34job = client.submit_async("gpt-image-1-mini", **payload)
35print(job.request_id)                         # available immediately
36try:
37    result = job.wait(timeout=600, interval=1.0)
38except InferenceTimeout as e:
39    print("still running:", e.request_id)
40except InferenceFailed as e:
41    print("failed:", e.detail)