Characters · REPRODUCIBLE GUIDE

Consistent Character Prompts: A Testable Character Sheet Method

Define identity anchors, wardrobe, views, and controlled variations for character consistency tests.

One API gateway for multiple AI models.

APIMart is a multi-model AI API gateway with an OpenAI-compatible endpoint. Use one account to access supported image models, compare current pricing, and choose a cost-efficient option for each workload.

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WHY THIS GUIDE EXISTS

Test the workflow,
not the marketing claim.

A method for separating stable character attributes from scene-specific variables.

Characters

Forest ranger character sheet

Character sheet for Mara, a forest ranger with cropped auburn hair, olive field jacket, brass compass and worn canvas backpack; front, profile and three-quarter views; neutral studio background; consistent facial features.
Identity consistency fixture3:2
Characters

Retro space mechanic

Full-body retro-futurist spacecraft mechanic, orange utility suit with modular pockets, grease marks, transparent helmet carried under one arm, practical silhouette, 1970s industrial science-fiction mood.
Full-body character concept2:3
Characters

Noir detective turnaround

Turnaround sheet for detective Imani Vale, short natural curls, charcoal trench coat, oxblood notebook, composed expression; front, side and back views; consistent proportions; soft gray studio background.
Three-view turnaround3:2
Characters

Children's book fox

Character reference for a curious red fox named Pip, oversized knitted blue scarf, small canvas satchel, rounded picture-book proportions, five clear expressions, watercolor and colored-pencil texture, white page.
Illustration identity anchor4:3
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,
)
REVIEW CHECKLIST

Before you publish a result