Flux Depth Dev 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-depth-dev",
 9    seed=85412,
10    prompt="spiderman lecture, photorealistic",
11    guidance=10,
12    megapixels="1",
13    num_outputs=1,
14    control_image="https://segmind-sd-models.s3.us-east-1.amazonaws.com/display_images/flux-tools/flux-dev-depth-ip-1.png",
15    output_format="jpg",
16    output_quality=80,
17    num_inference_steps=28,
18    disable_safety_checker=False,
19)
20print(result["status"])                      # COMPLETED
21print(result.get("output"))                  # model output (e.g. media URL)
22print(result["metrics"]["inference_time"])   # server compute seconds
23
24# --- Or submit + poll manually (track request_id, control the cadence) ---
25from segmind import SegmindClient, InferenceFailed, InferenceTimeout
26
27client = SegmindClient()                      # reads SEGMIND_API_KEY
28payload = {
29    "seed": 85412,
30    "prompt": "spiderman lecture, photorealistic",
31    "guidance": 10,
32    "megapixels": "1",
33    "num_outputs": 1,
34    "control_image": "https://segmind-sd-models.s3.us-east-1.amazonaws.com/display_images/flux-tools/flux-dev-depth-ip-1.png",
35    "output_format": "jpg",
36    "output_quality": 80,
37    "num_inference_steps": 28,
38    "disable_safety_checker": False,
39}
40job = client.submit_async("flux-depth-dev", **payload)
41print(job.request_id)                         # available immediately
42try:
43    result = job.wait(timeout=600, interval=1.0)
44except InferenceTimeout as e:
45    print("still running:", e.request_id)
46except InferenceFailed as e:
47    print("failed:", e.detail)