Mochi 1 Serverless API

 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3from segmind import SegmindClient, InferenceFailed, InferenceTimeout
 4
 5# Async (v2) — recommended for long-running / video models.
 6# run() blocks up to 600s; submit_async + job.wait(timeout=...) sets a longer
 7# deadline and keeps the request_id so you can re-poll later.
 8client = SegmindClient()                      # reads SEGMIND_API_KEY
 9payload = {
10    "prompt": "Create a short, looped animation of a small, fluffy creature with big, round eyes and soft fur, similar to a baby Pikachu, emulating the adorable curiosity of baby animals. The creature should be sitting in a human hand, surrounded by a soft, natural forest setting with tiny flowers and gentle lighting. Subtle, lifelike movements include slight head tilts, gentle blinking, and small, curious paw or ear twitches. Its large eyes should glimmer with curiosity and warmth, occasionally widening as it looks around its environment, embodying the innocent curiosity and playfulness of a young animal. Keep the lighting soft, creating a warm, inviting atmosphere with faint sunlight filtering through, highlighting the softness of its fur.",
11    "negative_prompt": "blurry, low quality, distorted wings",
12    "guidance_scale": 4.5,
13    "fps": 16,
14    "steps": 30,
15    "seed": 985521,
16    "frames": 52,
17}
18job = client.submit_async("mochi-1", **payload)
19print(job.request_id)                         # available immediately
20try:
21    result = job.wait(timeout=900, interval=2.0)
22    print(result["status"])                  # COMPLETED
23    print(result.get("output"))              # model output (e.g. video URL)
24except InferenceTimeout as e:
25    print("still running:", e.request_id)    # re-poll later with this id
26except InferenceFailed as e:
27    print("failed:", e.detail)
28
29# Fast models (<=600s) can use the one-liner instead:
30# result = segmind.run("mochi-1", **payload)