Test the workflow,
not the marketing claim.
Production error handling improves when permanent request failures are separated from temporary provider or network conditions, with safe prompt logging, stable job identifiers, retry budgets, and explicit terminal reasons for rejected assets.
Editorial product photograph of a matte ceramic skincare bottle on pale limestone, soft north-window light, delicate contact shadow, warm neutral palette, 85mm lens compression, no text, no logo.
Music festival poster
Experimental electronic music festival poster, oversized condensed type placeholders, electric blue field, silver halftone sphere, asymmetric Swiss grid, high contrast screen-print texture, leave all wording blank.
Transparent headphones cutout
Over-ear headphones isolated as a clean ecommerce cutout, transparent background, accurate soft edge detail around fabric ear pads, neutral product color, no floor, no text, no added accessories.
PYTHON QUICKSTART
Keep the request reproducible.
Store credentials in the environment. Record the exact model identifier, dimensions, test date, and retry count with the resulting asset.
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["APIMART_API_KEY"],
base_url="https://api.apimart.ai/v1",
)
result = client.images.generate(
model="gpt-image-1-official",
prompt=PROMPT,
size="1024x1024",
n=1,
)Before you publish a result
- Record model ID, parameters, date, latency, and retry count.
- Review instruction following and protected attributes.
- Flag invented text, marks, anatomy, or unwanted objects.
- Keep the raw output linked to the original fixture.
- Do not claim a universal winner from one prompt.