Flux Controlnets 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-controlnet",
 9    base64=False,
10    cn_stop=0.5,
11    cn_strength=0.4,
12    cn_type="pose",
13    custom_height=1024,
14    custom_width=1024,
15    guidance=3.5,
16    image="https://segmind-sd-models.s3.amazonaws.com/display_images/model_1.png",
17    image_format="jpeg",
18    prompt="Young woman in leather jacket and black mini skirt, busy city street, bokeh background, Kodak film, sunglasses on head, high quality photo, photorealistic, sharp focus, vibrant colors, urban fashion, street style, natural lighting, 35mm lens",
19    quality=95,
20    sampler="euler",
21    samples=1,
22    scheduler="simple",
23    seed=652889,
24    steps=20,
25    use_input_img_dimension=True,
26)
27print(result["status"])                      # COMPLETED
28print(result.get("output"))                  # model output (e.g. media URL)
29print(result["metrics"]["inference_time"])   # server compute seconds
30
31# --- Or submit + poll manually (track request_id, control the cadence) ---
32from segmind import SegmindClient, InferenceFailed, InferenceTimeout
33
34client = SegmindClient()                      # reads SEGMIND_API_KEY
35payload = {
36    "base64": False,
37    "cn_stop": 0.5,
38    "cn_strength": 0.4,
39    "cn_type": "pose",
40    "custom_height": 1024,
41    "custom_width": 1024,
42    "guidance": 3.5,
43    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/model_1.png",
44    "image_format": "jpeg",
45    "prompt": "Young woman in leather jacket and black mini skirt, busy city street, bokeh background, Kodak film, sunglasses on head, high quality photo, photorealistic, sharp focus, vibrant colors, urban fashion, street style, natural lighting, 35mm lens",
46    "quality": 95,
47    "sampler": "euler",
48    "samples": 1,
49    "scheduler": "simple",
50    "seed": 652889,
51    "steps": 20,
52    "use_input_img_dimension": True,
53}
54job = client.submit_async("flux-controlnet", **payload)
55print(job.request_id)                         # available immediately
56try:
57    result = job.wait(timeout=600, interval=1.0)
58except InferenceTimeout as e:
59    print("still running:", e.request_id)
60except InferenceFailed as e:
61    print("failed:", e.detail)