Qwen Image 3.0 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    "qwen-image-3",
 9    prompt="A cozy independent bookstore cafe on a rainy autumn evening, warm golden light glowing through the large front windows onto a wet cobblestone street, a hand-painted wooden sign above the entrance that reads \"Qwen Books & Coffee\", reflections shimmering in the puddles, a person under a red umbrella walking past, cinematic photorealistic detail, shallow depth of field, 35mm",
10    size="1328*1328",
11    negative_prompt="blurry, watermark, low quality, distorted text, deformed, extra limbs, jpeg artifacts",
12    prompt_extend=True,
13    prompt_extend_mode="direct",
14    seed=12345,
15    watermark=False,
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": "A cozy independent bookstore cafe on a rainy autumn evening, warm golden light glowing through the large front windows onto a wet cobblestone street, a hand-painted wooden sign above the entrance that reads \"Qwen Books & Coffee\", reflections shimmering in the puddles, a person under a red umbrella walking past, cinematic photorealistic detail, shallow depth of field, 35mm",
27    "size": "1328*1328",
28    "negative_prompt": "blurry, watermark, low quality, distorted text, deformed, extra limbs, jpeg artifacts",
29    "prompt_extend": True,
30    "prompt_extend_mode": "direct",
31    "seed": 12345,
32    "watermark": False,
33}
34job = client.submit_async("qwen-image-3", **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)