Flux.1 Image To Image 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-img2img",
 9    prompt="anime style",
10    image="https://segmind-sd-models.s3.amazonaws.com/display_images/flux-i2i-ip.png",
11    steps=20,
12    seed=46588,
13    denoise=0.75,
14    scheduler="simple",
15    sampler_name="euler",
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    "prompt": "anime style",
28    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/flux-i2i-ip.png",
29    "steps": 20,
30    "seed": 46588,
31    "denoise": 0.75,
32    "scheduler": "simple",
33    "sampler_name": "euler",
34    "base64": False,
35}
36job = client.submit_async("flux-img2img", **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)