Runway Gen 4 Image 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    "runway-gen4-image",
 9    promptText="photo of a model wearing a cloth and standing in a garden.",
10    referenceImages=[{"uri": "https://segmind-inference-inputs.s3.amazonaws.com/c226e2cf-49ea-4b8d-a630-9847c0efbbce-Beach-walk.png", "tag": "model"}, {"uri": "https://segmind-resources.s3.amazonaws.com/output/cfda480d-86f3-4230-aed3-fcfae874df3b-saree.webp", "tag": "cloth"}],
11    ratio="1280:720",
12)
13print(result["status"])                      # COMPLETED
14print(result.get("output"))                  # model output (e.g. media URL)
15print(result["metrics"]["inference_time"])   # server compute seconds
16
17# --- Or submit + poll manually (track request_id, control the cadence) ---
18from segmind import SegmindClient, InferenceFailed, InferenceTimeout
19
20client = SegmindClient()                      # reads SEGMIND_API_KEY
21payload = {
22    "promptText": "photo of a model wearing a cloth and standing in a garden.",
23    "referenceImages": [{"uri": "https://segmind-inference-inputs.s3.amazonaws.com/c226e2cf-49ea-4b8d-a630-9847c0efbbce-Beach-walk.png", "tag": "model"}, {"uri": "https://segmind-resources.s3.amazonaws.com/output/cfda480d-86f3-4230-aed3-fcfae874df3b-saree.webp", "tag": "cloth"}],
24    "ratio": "1280:720",
25}
26job = client.submit_async("runway-gen4-image", **payload)
27print(job.request_id)                         # available immediately
28try:
29    result = job.wait(timeout=600, interval=1.0)
30except InferenceTimeout as e:
31    print("still running:", e.request_id)
32except InferenceFailed as e:
33    print("failed:", e.detail)