FLUX 3 Image Edit 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    "flux-3-image-edit",
 9    images=["https://segmind-resources.s3.amazonaws.com/input/flux-3-image-edit-garage-src-6af504cd.jpg"],
10    prompt="Recolour only the motorcycle's fuel tank from cherry red to brushed copper. Keep the chrome, the tyres, the pegboard of hand tools, the brick wall and the lighting exactly unchanged.",
11    resolution="1k",
12    aspect_ratio="auto",
13    safety_tolerance=2,
14    grounding=True,
15)
16print(result["status"])                      # COMPLETED
17print(result.get("output"))                  # model output (e.g. media URL)
18print(result["metrics"]["inference_time"])   # server compute seconds
19
20# --- Or submit + poll manually (track request_id, control the cadence) ---
21from segmind import SegmindClient, InferenceFailed, InferenceTimeout
22
23client = SegmindClient()                      # reads SEGMIND_API_KEY
24payload = {
25    "images": ["https://segmind-resources.s3.amazonaws.com/input/flux-3-image-edit-garage-src-6af504cd.jpg"],
26    "prompt": "Recolour only the motorcycle's fuel tank from cherry red to brushed copper. Keep the chrome, the tyres, the pegboard of hand tools, the brick wall and the lighting exactly unchanged.",
27    "resolution": "1k",
28    "aspect_ratio": "auto",
29    "safety_tolerance": 2,
30    "grounding": True,
31}
32job = client.submit_async("flux-3-image-edit", **payload)
33print(job.request_id)                         # available immediately
34try:
35    result = job.wait(timeout=600, interval=1.0)
36except InferenceTimeout as e:
37    print("still running:", e.request_id)
38except InferenceFailed as e:
39    print("failed:", e.detail)