Consistent Character V1 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    "consistent-character-ai-neolemon",
 9    prompt="((masterpiece, best quality, highly detailed)), simple background, character sheet, multiple poses, multiple actions, visible face, (one person), portrait, full body, young african american girl, white sweater, jeans, short curly brown hair, 2D illustration style",
10    negative_prompt="text, watermark, underexposed, ugly, jpeg, (worst quality, low quality, lowres, low details, oversaturated, undersaturated, overexposed, grayscale, bw, bad photo, bad art:1.4), (font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), cropped, out of frame, cut off, jpeg artifacts, out of focus, glitch, duplicate, (amateur:1.3), merging, clipping, (nsfw), multiple hands, mutant, glitch, uncanny, cross eye, broken face, astronaut, helmet, blurry,",
11    image="https://segmind-sd-models.s3.amazonaws.com/display_images/testing_imgs/ref.pose.png",
12    num_inference_steps=20,
13    guidance_scale=7,
14    seed=4898558797,
15    samples=1,
16    strength=0.8,
17    scheduler="karras",
18    sampler="dpmpp_2m",
19    upscale_by=2,
20    upscale_steps=20,
21    upscale_guidance_scale=7,
22    upscale_scheduler="karras",
23    upscale_sampler="dpmpp_2m",
24    upscale_mode_type="Linear",
25    fd_steps=20,
26    fd_guidance_scale=7,
27    fd_scheduler="karras",
28    fd_sampler="dpmpp_2m",
29)
30print(result["status"])                      # COMPLETED
31print(result.get("output"))                  # model output (e.g. media URL)
32print(result["metrics"]["inference_time"])   # server compute seconds
33
34# --- Or submit + poll manually (track request_id, control the cadence) ---
35from segmind import SegmindClient, InferenceFailed, InferenceTimeout
36
37client = SegmindClient()                      # reads SEGMIND_API_KEY
38payload = {
39    "prompt": "((masterpiece, best quality, highly detailed)), simple background, character sheet, multiple poses, multiple actions, visible face, (one person), portrait, full body, young african american girl, white sweater, jeans, short curly brown hair, 2D illustration style",
40    "negative_prompt": "text, watermark, underexposed, ugly, jpeg, (worst quality, low quality, lowres, low details, oversaturated, undersaturated, overexposed, grayscale, bw, bad photo, bad art:1.4), (font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), cropped, out of frame, cut off, jpeg artifacts, out of focus, glitch, duplicate, (amateur:1.3), merging, clipping, (nsfw), multiple hands, mutant, glitch, uncanny, cross eye, broken face, astronaut, helmet, blurry,",
41    "image": "https://segmind-sd-models.s3.amazonaws.com/display_images/testing_imgs/ref.pose.png",
42    "num_inference_steps": 20,
43    "guidance_scale": 7,
44    "seed": 4898558797,
45    "samples": 1,
46    "strength": 0.8,
47    "scheduler": "karras",
48    "sampler": "dpmpp_2m",
49    "upscale_by": 2,
50    "upscale_steps": 20,
51    "upscale_guidance_scale": 7,
52    "upscale_scheduler": "karras",
53    "upscale_sampler": "dpmpp_2m",
54    "upscale_mode_type": "Linear",
55    "fd_steps": 20,
56    "fd_guidance_scale": 7,
57    "fd_scheduler": "karras",
58    "fd_sampler": "dpmpp_2m",
59}
60job = client.submit_async("consistent-character-ai-neolemon", **payload)
61print(job.request_id)                         # available immediately
62try:
63    result = job.wait(timeout=600, interval=1.0)
64except InferenceTimeout as e:
65    print("still running:", e.request_id)
66except InferenceFailed as e:
67    print("failed:", e.detail)