ClarityAI Flux Upscaler 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    "clarityai-flux-upscaler",
 9    image="https://segmind-resources.s3.amazonaws.com/input/d394591c-4f41-448a-83ba-2f899674116f-output-1762260846988.png",
10    scale_factor=4,
11    creativity=3,
12    prompt="A serene landscape with mountains and a clear sky.",
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    "image": "https://segmind-resources.s3.amazonaws.com/input/d394591c-4f41-448a-83ba-2f899674116f-output-1762260846988.png",
24    "scale_factor": 4,
25    "creativity": 3,
26    "prompt": "A serene landscape with mountains and a clear sky.",
27}
28job = client.submit_async("clarityai-flux-upscaler", **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)