Bria 3.2 Text to 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    "bria-text-to-image",
 9    prompt="A professional headshot of a CEO",
10    mode="base",
11    aspect_ratio="1:1",
12    seed=654321,
13    negative_prompt="no storms",
14    steps_num=40,
15    text_guidance_scale=7,
16    medium="photography",
17    prompt_enhancement=True,
18    enhance_image=True,
19    prompt_content_moderation=True,
20    content_moderation=False,
21    ip_signal=False,
22)
23print(result["status"])                      # COMPLETED
24print(result.get("output"))                  # model output (e.g. media URL)
25print(result["metrics"]["inference_time"])   # server compute seconds
26
27# --- Or submit + poll manually (track request_id, control the cadence) ---
28from segmind import SegmindClient, InferenceFailed, InferenceTimeout
29
30client = SegmindClient()                      # reads SEGMIND_API_KEY
31payload = {
32    "prompt": "A professional headshot of a CEO",
33    "mode": "base",
34    "aspect_ratio": "1:1",
35    "seed": 654321,
36    "negative_prompt": "no storms",
37    "steps_num": 40,
38    "text_guidance_scale": 7,
39    "medium": "photography",
40    "prompt_enhancement": True,
41    "enhance_image": True,
42    "prompt_content_moderation": True,
43    "content_moderation": False,
44    "ip_signal": False,
45}
46job = client.submit_async("bria-text-to-image", **payload)
47print(job.request_id)                         # available immediately
48try:
49    result = job.wait(timeout=600, interval=1.0)
50except InferenceTimeout as e:
51    print("still running:", e.request_id)
52except InferenceFailed as e:
53    print("failed:", e.detail)