PuLID Lightning 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    "pulid-lightning",
 9    seed=412431,
10    width=1024,
11    height=1024,
12    prompt="A photo of a person",
13    face_image="https://segmind-sd-models.s3.amazonaws.com/display_images/Pid_ip.png.png",
14    face_style="high-fidelity",
15    output_format="png",
16    output_quality=80,
17    checkpoint_model="default",
18    number_of_images=1,
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": 412431,
30    "width": 1024,
31    "height": 1024,
32    "prompt": "A photo of a person",
33    "face_image": "https://segmind-sd-models.s3.amazonaws.com/display_images/Pid_ip.png.png",
34    "face_style": "high-fidelity",
35    "output_format": "png",
36    "output_quality": 80,
37    "checkpoint_model": "default",
38    "number_of_images": 1,
39}
40job = client.submit_async("pulid-lightning", **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)