Sarvam Bulbul v3 TTS 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    "sarvam-bulbul-v3-tts",
 9    text="नमस्ते! सेगमाइंड में आपका स्वागत है। आज हम भारतीय भाषाओं के लिए natural text-to-speech का demo देखेंगे।",
10    language_code="hi-IN",
11    speaker="shubh",
12    pace=1,
13    temperature=0.6,
14    output_audio_codec="wav",
15    speech_sample_rate=24000,
16)
17print(result["status"])                      # COMPLETED
18print(result.get("output"))                  # model output (e.g. media URL)
19print(result["metrics"]["inference_time"])   # server compute seconds
20
21# --- Or submit + poll manually (track request_id, control the cadence) ---
22from segmind import SegmindClient, InferenceFailed, InferenceTimeout
23
24client = SegmindClient()                      # reads SEGMIND_API_KEY
25payload = {
26    "text": "नमस्ते! सेगमाइंड में आपका स्वागत है। आज हम भारतीय भाषाओं के लिए natural text-to-speech का demo देखेंगे।",
27    "language_code": "hi-IN",
28    "speaker": "shubh",
29    "pace": 1,
30    "temperature": 0.6,
31    "output_audio_codec": "wav",
32    "speech_sample_rate": 24000,
33}
34job = client.submit_async("sarvam-bulbul-v3-tts", **payload)
35print(job.request_id)                         # available immediately
36try:
37    result = job.wait(timeout=600, interval=1.0)
38except InferenceTimeout as e:
39    print("still running:", e.request_id)
40except InferenceFailed as e:
41    print("failed:", e.detail)