Dia (Text to Speech) 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    "dia",
 9    text="[S1] Segmind lets you build powerful image and video workflows — no code needed. \n [S2] Over 200 open and closed models. Just drag, drop, and deploy. \n [S1] Wait, seriously? Even custom models? \n [S2] Yup. Even fine-tuned ones. (chuckles) \n [S1] That's wild. I’ve spent weeks writing code for this. \n [S2] Now you can do it in minutes. Go try Segmind on the cloud. \n  [S1] I'm sold. Let’s go. (laughs)",
10    top_p=0.95,
11    cfg_scale=4,
12    temperature=1.3,
13    input_audio="https://segmind-resources.s3.amazonaws.com/input/7d11a77b-366c-406e-b6af-eefaec4f8574-fa3123db-56cf-4212-9cc9-ebc49e692202-04fc4d16-25df-44cb-9b7c-37aa7543e6d2.wav",
14    speed_factor=0.94,
15    max_new_tokens=3072,
16    cfg_filter_top_k=35,
17)
18print(result["status"])                      # COMPLETED
19print(result.get("output"))                  # model output (e.g. media URL)
20print(result["metrics"]["inference_time"])   # server compute seconds
21
22# --- Or submit + poll manually (track request_id, control the cadence) ---
23from segmind import SegmindClient, InferenceFailed, InferenceTimeout
24
25client = SegmindClient()                      # reads SEGMIND_API_KEY
26payload = {
27    "text": "[S1] Segmind lets you build powerful image and video workflows — no code needed. \n [S2] Over 200 open and closed models. Just drag, drop, and deploy. \n [S1] Wait, seriously? Even custom models? \n [S2] Yup. Even fine-tuned ones. (chuckles) \n [S1] That's wild. I’ve spent weeks writing code for this. \n [S2] Now you can do it in minutes. Go try Segmind on the cloud. \n  [S1] I'm sold. Let’s go. (laughs)",
28    "top_p": 0.95,
29    "cfg_scale": 4,
30    "temperature": 1.3,
31    "input_audio": "https://segmind-resources.s3.amazonaws.com/input/7d11a77b-366c-406e-b6af-eefaec4f8574-fa3123db-56cf-4212-9cc9-ebc49e692202-04fc4d16-25df-44cb-9b7c-37aa7543e6d2.wav",
32    "speed_factor": 0.94,
33    "max_new_tokens": 3072,
34    "cfg_filter_top_k": 35,
35}
36job = client.submit_async("dia", **payload)
37print(job.request_id)                         # available immediately
38try:
39    result = job.wait(timeout=600, interval=1.0)
40except InferenceTimeout as e:
41    print("still running:", e.request_id)
42except InferenceFailed as e:
43    print("failed:", e.detail)