GPT Image 2 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-2",
 9    size="1536x1024",
10    prompt="A photorealistic, cinematic shot of a cozy independent bookstore in Mumbai at golden hour. Warm afternoon sunlight streams through a tall front window onto wooden shelves packed with books; book spines are clearly visible with titles in English and Hindi Devanagari script. In the foreground, a handwritten chalkboard A-frame easel reads, in clean legible chalk lettering: first line 'मुंबई पुस्तक भंडार', second line 'Mumbai Book Store', and a smaller third line 'Open Daily  9 am – 9 pm'. Shallow depth of field, shot on a full-frame camera at 35mm f/2.0, ultra-realistic detail, natural color grading, dust motes in sunlight, film grain.",
11    quality="high",
12    background="opaque",
13    image_urls=[],
14    moderation="auto",
15    output_format="png",
16    output_compression=100,
17)
18print(result["status"])                      # COMPLETED
19print(result.get("output"))                  # model output (e.g. media URL)
20print(result["metrics"]["inference_time"])   # server compute seconds
21
22# --- Or submit + poll manually (track request_id, control the cadence) ---
23from segmind import SegmindClient, InferenceFailed, InferenceTimeout
24
25client = SegmindClient()                      # reads SEGMIND_API_KEY
26payload = {
27    "size": "1536x1024",
28    "prompt": "A photorealistic, cinematic shot of a cozy independent bookstore in Mumbai at golden hour. Warm afternoon sunlight streams through a tall front window onto wooden shelves packed with books; book spines are clearly visible with titles in English and Hindi Devanagari script. In the foreground, a handwritten chalkboard A-frame easel reads, in clean legible chalk lettering: first line 'मुंबई पुस्तक भंडार', second line 'Mumbai Book Store', and a smaller third line 'Open Daily  9 am – 9 pm'. Shallow depth of field, shot on a full-frame camera at 35mm f/2.0, ultra-realistic detail, natural color grading, dust motes in sunlight, film grain.",
29    "quality": "high",
30    "background": "opaque",
31    "image_urls": [],
32    "moderation": "auto",
33    "output_format": "png",
34    "output_compression": 100,
35}
36job = client.submit_async("gpt-image-2", **payload)
37print(job.request_id)                         # available immediately
38try:
39    result = job.wait(timeout=600, interval=1.0)
40except InferenceTimeout as e:
41    print("still running:", e.request_id)
42except InferenceFailed as e:
43    print("failed:", e.detail)