LTX-2-19B T2V 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": "A dynamic medium shot of a young Indian woman in casual streetwear walking quickly toward the camera through a modern tech office corridor, eyes wide with excitement, gesturing with her hands as she talks, bright daytime fluorescent lighting, smooth handheld tracking shot that keeps her centered in frame, colleagues and Segmind branding softly blurred in the background, natural office ambience as she walks and excitedly shouts in clear Indian English: 'L T X 2 video model is superfast, check it out its live on segmind'",
11    "negative_prompt": "blurry, low quality, still frame, frames, watermark, overlay, titles, has blurbox, has subtitles",
12    "width": 720,
13    "height": 1280,
14    "num_frames": 121,
15    "fps": 24,
16    "seed": 1234567890,
17    "guidance_scale": 4,
18}
19job = client.submit_async("ltx-2-19b-t2v", **payload)
20print(job.request_id)                         # available immediately
21try:
22    result = job.wait(timeout=900, interval=2.0)
23    print(result["status"])                  # COMPLETED
24    print(result.get("output"))              # model output (e.g. video URL)
25except InferenceTimeout as e:
26    print("still running:", e.request_id)    # re-poll later with this id
27except InferenceFailed as e:
28    print("failed:", e.detail)
29
30# Fast models (<=600s) can use the one-liner instead:
31# result = segmind.run("ltx-2-19b-t2v", **payload)