Nano Banana 2.1 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    "nano-banana-2.1",
 9    prompt="A clean educational infographic: a cross-section cutaway of an erupting stratovolcano against a pale grid background. The cutaway reveals the interior with neat leader lines connecting to legible labels reading 'MAGMA CHAMBER', 'CENTRAL VENT', 'SIDE VENT', 'LAVA FLOW', 'ASH CLOUD', and 'ROCK STRATA'. A bold title 'ANATOMY OF A VOLCANO' runs across the top, with a small compass rose and a scale bar in the lower corner. Flat vector illustration style with layered rock colours and a rising ash plume.",
10    image_urls=[],
11    system_prompt="",
12    aspect_ratio="4:3",
13    output_resolution="2K",
14    output_format="png",
15    web_search=False,
16    response_modalities="TEXT_AND_IMAGE",
17    seed=420875,
18    thinking_level="high",
19    safety_tolerance=4,
20)
21print(result["status"])                      # COMPLETED
22print(result.get("output"))                  # model output (e.g. media URL)
23print(result["metrics"]["inference_time"])   # server compute seconds
24
25# --- Or submit + poll manually (track request_id, control the cadence) ---
26from segmind import SegmindClient, InferenceFailed, InferenceTimeout
27
28client = SegmindClient()                      # reads SEGMIND_API_KEY
29payload = {
30    "prompt": "A clean educational infographic: a cross-section cutaway of an erupting stratovolcano against a pale grid background. The cutaway reveals the interior with neat leader lines connecting to legible labels reading 'MAGMA CHAMBER', 'CENTRAL VENT', 'SIDE VENT', 'LAVA FLOW', 'ASH CLOUD', and 'ROCK STRATA'. A bold title 'ANATOMY OF A VOLCANO' runs across the top, with a small compass rose and a scale bar in the lower corner. Flat vector illustration style with layered rock colours and a rising ash plume.",
31    "image_urls": [],
32    "system_prompt": "",
33    "aspect_ratio": "4:3",
34    "output_resolution": "2K",
35    "output_format": "png",
36    "web_search": False,
37    "response_modalities": "TEXT_AND_IMAGE",
38    "seed": 420875,
39    "thinking_level": "high",
40    "safety_tolerance": 4,
41}
42job = client.submit_async("nano-banana-2.1", **payload)
43print(job.request_id)                         # available immediately
44try:
45    result = job.wait(timeout=600, interval=1.0)
46except InferenceTimeout as e:
47    print("still running:", e.request_id)
48except InferenceFailed as e:
49    print("failed:", e.detail)