Qwen Image Edit Fast 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-edit-fast",
 9    image="https://segmind-resources.s3.amazonaws.com/input/354cdf06-8901-4f0c-a9e0-8bf72bcb2859-5769d60b13eeba42135ff0c65db49c14.png",
10    prompt="Change '1000$' to '5$' in the poster",
11    steps=8,
12    guidance=1,
13    seed=760941192,
14    image_format="png",
15    quality=90,
16    base64=False,
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    "image": "https://segmind-resources.s3.amazonaws.com/input/354cdf06-8901-4f0c-a9e0-8bf72bcb2859-5769d60b13eeba42135ff0c65db49c14.png",
28    "prompt": "Change '1000$' to '5$' in the poster",
29    "steps": 8,
30    "guidance": 1,
31    "seed": 760941192,
32    "image_format": "png",
33    "quality": 90,
34    "base64": False,
35}
36job = client.submit_async("qwen-image-edit-fast", **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)