| name | AI Character Reference Generation |
| description | Generate consistent visual character references across multiple scenarios using Flux and nano-banana-pro on Replicate |
| applyTo | **/*character*,**/*reference*,**/*generate*,**/*replicate*,**/*avatar*,**/*portrait* |
| triggers | ["generate character","create character","character image","generate portrait","create portrait","generate avatar","create avatar","generate photo","ai portrait","ai avatar","replicate","flux","nano-banana","face consistency","reference face","profile picture","headshot"] |
AI Character Reference Generation
Create 17+ consistent character poses from detailed prompts — no reference images needed.
⚠️ Staleness Watch (Last validated: Feb 2026 — Flux 1.1 Pro): Image generation models on Replicate release new versions and deprecate old ones. Before generating, verify the model identifier at replicate.com/black-forest-labs. Upgrade path: black-forest-labs/flux-1.1-pro-ultra provides higher resolution (up to 4MP) with the same API surface. Input parameter schema may change between model versions.
Model Selection Guide
Recommended Models by Use Case
| Use Case | Model | Cost | Notes |
|---|
| Face Consistency (Default) | google/nano-banana-pro | $0.025/image | Best for maintaining face identity — uses reference image + prompt. Maintains Alex identity across 90+ avatar images. |
| Detailed Scenes | black-forest-labs/flux-1.1-pro | $0.04/image | High-quality scenes without face reference. Good for backgrounds and environments. |
| Agent Banners | ideogram-ai/ideogram-v2 | $0.08/image | Best for stylized text + character combinations. Prominent branding. |
| High Resolution | black-forest-labs/flux-1.1-pro-ultra | $0.06/image | Up to 4MP output. Use when print-quality needed. |
Face Consistency Pattern (Nano-Banana Pro)
The Key Insight: For consistent character faces across multiple poses/scenarios, use a reference face image with nano-banana-pro:
const response = await replicate.run("google/nano-banana-pro", {
input: {
prompt: `${CHARACTER_DESC}, ${scenario.attire}, ${scenario.pose}, ${STYLE}`,
image: await toDataURI("path/to/reference-face.png"),
aspect_ratio: "1:1",
output_format: "png"
}
});
Cost Analysis:
- 90 avatar images × $0.025 = $2.25 total (nano-banana)
- vs 90 × $0.04 = $3.60 (Flux 1.1 Pro)
- Savings: 37.5% while maintaining face consistency
Summary
Complete workflow for generating consistent visual character references across multiple scenarios using Flux 1.1 Pro API. Validated through 51 successful image generations across 3 character types.
Critical Insight: Character Consistency Without Reference Images
Common Misconception: Use image_prompt parameter with reference photo for consistency
Reality:
image_prompt = Flux Redux composition guidance (NOT character consistency)- Character consistency comes from detailed text descriptions
- Pose variety comes from explicit body position descriptions
Prompt Engineering Pattern
const PROMPT_TEMPLATE = `
${CHARACTER_DESC}, // Detailed physical description
${scenario.attire}, // Scene-appropriate clothing
${scenario.scenario}, // Narrative context
${scenario.pose}, // EXPLICIT body position/gesture
${scenario.environment}, // Setting details
${scenario.lighting}, // Light sources and mood
${scenario.mood}, // Emotional tone
${STYLE_BASE} // Aesthetic/rendering style
`;
Critical Success Factors
-
Detailed CHARACTER_DESC (creates consistency):
const CHARACTER_DESC = "Alex Finch, 21, sharp intelligent features, " +
"short dark brown hair with copper highlights, athletic build, " +
"confident but approachable demeanor, piercing analytical eyes";
-
Explicit Pose Descriptions (creates variety):
- ❌ Vague: "standing in office"
- ✅ Specific: "leaning forward with both hands on desk, analyzing data intently"
- ✅ Specific: "standing with one hand gesturing toward display, explaining concept"
-
Style Consistency:
const STYLE_BASE = "Professional illustration, high contrast noir lighting, " +
"dramatic shadows, cinematic composition, sharp detail, moody atmosphere";
const STYLE_BASE = "Soft fantasy illustration, pastel color harmony, " +
"ethereal glow, magical atmosphere, dreamy composition";
Character-Agnostic Template Structure
const CHARACTER = {
name: "Character Name",
description: "detailed physical appearance",
age: number
};
const STYLE = "aesthetic appropriate to narrative";
const SCENARIOS = [
{
id: "001",
title: "Scene Title",
scenario: "narrative context",
attire: "specific clothing details",
pose: "EXPLICIT body position, hands, gaze",
environment: "setting details",
lighting: "light sources and mood",
mood: "emotional tone"
}
];
async function generateScene(scenario) {
const prompt = buildPrompt(CHARACTER, scenario, STYLE);
return await replicate.run("black-forest-labs/flux-1.1-pro", {
input: {
prompt,
aspect_ratio: "3:4",
output_format: "png",
output_quality: 100,
safety_tolerance: 2
}
});
}
Validated Results
Successful Generations (Feb 2026):
- Alex: 17/17 professional noir scenes
- Iris: 17/17 wonderland magic scenes
- Maya: 17/17 teen life scenes
Quality Metrics:
- 100% generation success rate (with retry handling)
- 17 unique poses per character
- Visual consistency maintained across all images
- Style consistency within each aesthetic type
Troubleshooting
Safety Filter False Positives
Issue: Child character poses sometimes trigger safety filters
Example: "sitting on ground, knees drawn up" (blocked)
Solution: Adjust to neutral poses: "sitting cross-legged leaning forward"
Pattern: Avoid poses that could be misinterpreted for child characters
Rate Limiting
Issue: 429 Too Many Requests from Replicate API
Solution: Exponential backoff retry pattern
async function retryWithBackoff(fn, maxRetries = 3) {
for (let i = 0; i < maxRetries; i++) {
try {
return await fn();
} catch (error) {
if (error.response?.status === 429 && i < maxRetries - 1) {
const delay = 2000 * Math.pow(2, i);
await new Promise(r => setTimeout(r, delay));
continue;
}
throw error;
}
}
}
Pose Repetition
Symptom: All images show similar body positions
Diagnosis: Pose descriptions too vague
Fix: Be cinematically specific
- ✅ "leaning against doorframe, arms crossed, skeptical expression"
- ✅ "crouched examining ground, one hand touching surface"
- ✅ "mid-stride walking forward, confident purposeful movement"
Cost and Performance
Default: Nano-Banana Pro (Face Consistency)
- Model:
google/nano-banana-pro (recommended)
- Cost: $0.025 per image
- Generation Time: ~15-30 seconds per image
- Best For: Character avatars, portraits, face consistency
- Requires: Reference face image
Alternative: Flux 1.1 Pro (Scene Flexibility)
- Model:
black-forest-labs/flux-1.1-pro
- Cost: $0.04 per image
- Generation Time: ~30-60 seconds per image
- Best For: Full scenes, no reference image needed
- Aspect Ratio: 3:4 portrait recommended
- Output Format: PNG at quality 100 for archival
Economic Comparison:
| Character Set | Nano-Banana | Flux 1.1 Pro |
|---|
| 17 scenarios | $0.43 | $0.68 |
| 90 avatars | $2.25 | $3.60 |
| Full set (100+) | ~$2.50 | ~$4.00 |
Cross-Project Applicability
Use Cases:
- Book character reference sheets
- Visual novel character consistency
- Game concept art
- Marketing material uniformity
- Story illustration preparation
Character Types Validated:
- Young adult detective (noir aesthetic)
- Teen fantasy character (ethereal aesthetic)
- Contemporary teenager (realistic aesthetic)
Implementation
Dependencies:
- Replicate API account and token
- Node.js with ES modules support
File Organization:
characters/
{character-slug}/
images/
{collection-name}/
001-{scenario-title}.png
002-{scenario-title}.png
generation-report.json
Package.json script:
"scripts": {
"generate:character": "node scripts/generate-character-reference.js"
}
Confidence Level
High — Empirically validated through:
- 51 successful image generations
- 3 different character types
- 3 different aesthetic styles
- 100% success rate (with retry handling)
