Krea 3 Text to Image 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    "krea-3-text-to-image",
 9    prompt="Roller derby jam on a banked wooden track: a jammer in a star-marked helmet cover bursts through a wall of three blockers, one blocker sliding on a knee pad. Roster numbers printed large on their arms and mesh tank jerseys read '07', '22', and '14'. Motion blur streaks off the spinning wheels while the skaters' bodies stay sharp; sweat, scuffed floor tape, taped-up pads. Direct on-camera flash, dark packed crowd behind, 35mm documentary sports photograph.",
10    resolution="2k",
11    aspect_ratio="3:2",
12    thinking_mode="high",
13)
14print(result["status"])                      # COMPLETED
15print(result.get("output"))                  # model output (e.g. media URL)
16print(result["metrics"]["inference_time"])   # server compute seconds
17
18# --- Or submit + poll manually (track request_id, control the cadence) ---
19from segmind import SegmindClient, InferenceFailed, InferenceTimeout
20
21client = SegmindClient()                      # reads SEGMIND_API_KEY
22payload = {
23    "prompt": "Roller derby jam on a banked wooden track: a jammer in a star-marked helmet cover bursts through a wall of three blockers, one blocker sliding on a knee pad. Roster numbers printed large on their arms and mesh tank jerseys read '07', '22', and '14'. Motion blur streaks off the spinning wheels while the skaters' bodies stay sharp; sweat, scuffed floor tape, taped-up pads. Direct on-camera flash, dark packed crowd behind, 35mm documentary sports photograph.",
24    "resolution": "2k",
25    "aspect_ratio": "3:2",
26    "thinking_mode": "high",
27}
28job = client.submit_async("krea-3-text-to-image", **payload)
29print(job.request_id)                         # available immediately
30try:
31    result = job.wait(timeout=600, interval=1.0)
32except InferenceTimeout as e:
33    print("still running:", e.request_id)
34except InferenceFailed as e:
35    print("failed:", e.detail)