Text Embedding 3 Large 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    "text-embedding-3-large",
 9    prompt="You are beautiful",
10)
11print(result["status"])                      # COMPLETED
12print(result.get("output"))                  # model output (e.g. media URL)
13print(result["metrics"]["inference_time"])   # server compute seconds
14
15# --- Or submit + poll manually (track request_id, control the cadence) ---
16from segmind import SegmindClient, InferenceFailed, InferenceTimeout
17
18client = SegmindClient()                      # reads SEGMIND_API_KEY
19payload = {
20    "prompt": "You are beautiful",
21}
22job = client.submit_async("text-embedding-3-large", **payload)
23print(job.request_id)                         # available immediately
24try:
25    result = job.wait(timeout=600, interval=1.0)
26except InferenceTimeout as e:
27    print("still running:", e.request_id)
28except InferenceFailed as e:
29    print("failed:", e.detail)