ideogram-reference-architecture
Implement Ideogram reference architecture with prompt templates, asset pipelines, and CDN delivery. Use when designing new Ideogram integrations, building brand asset systems, or establishing architecture for image generation at scale. Trigger with phrases like "ideogram architecture", "ideogram project structure", "ideogram brand assets", "ideogram pipeline design", "ideogram at scale".
Best use case
ideogram-reference-architecture is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Implement Ideogram reference architecture with prompt templates, asset pipelines, and CDN delivery. Use when designing new Ideogram integrations, building brand asset systems, or establishing architecture for image generation at scale. Trigger with phrases like "ideogram architecture", "ideogram project structure", "ideogram brand assets", "ideogram pipeline design", "ideogram at scale".
Teams using ideogram-reference-architecture should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ideogram-reference-architecture/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ideogram-reference-architecture Compares
| Feature / Agent | ideogram-reference-architecture | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Implement Ideogram reference architecture with prompt templates, asset pipelines, and CDN delivery. Use when designing new Ideogram integrations, building brand asset systems, or establishing architecture for image generation at scale. Trigger with phrases like "ideogram architecture", "ideogram project structure", "ideogram brand assets", "ideogram pipeline design", "ideogram at scale".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Ideogram Reference Architecture
## Overview
Production architecture for AI image generation with Ideogram at scale. Covers prompt templating for brand consistency, generation pipelines using all six API endpoints, asset storage and CDN delivery, and metadata tracking for reproducibility.
## Architecture Diagram
```
┌─────────────────────────────────────────────────────────┐
│ Prompt Engineering Layer │
│ Templates │ Brand Guidelines │ Negative Prompts │
└──────────────────────────┬──────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────┐
│ Ideogram API (api.ideogram.ai) │
│ ┌──────────┐ ┌────────┐ ┌───────┐ ┌────────┐ │
│ │ Generate │ │ Edit │ │ Remix │ │Describe│ │
│ │(text→img)│ │(inpaint)│ │(vary) │ │(img→txt)│ │
│ └────┬─────┘ └───┬────┘ └──┬────┘ └───┬────┘ │
│ │ │ │ │ │
│ ┌────┴───────────┴─────────┴──────────┘ │
│ │ ┌──────────┐ ┌─────────┐ │
│ │ │ Upscale │ │ Reframe │ │
│ │ └────┬─────┘ └────┬────┘ │
│ └───────┴──────────────┘ │
└──────────────────────────┬──────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────┐
│ Post-Processing & Storage │
│ Download │ Resize │ WebP Convert │ S3/GCS │ CDN │
└─────────────────────────────────────────────────────────┘
```
## Instructions
### Step 1: Prompt Template System
```typescript
interface PromptTemplate {
name: string;
base: string;
style: string;
negativePrompt: string;
aspectRatio: string;
model: string;
renderingSpeed?: string;
}
const BRAND_TEMPLATES: Record<string, PromptTemplate> = {
socialPost: {
name: "Social Media Post",
base: "{subject}, modern clean design, vibrant colors, professional",
style: "DESIGN",
negativePrompt: "blurry text, misspelled, watermark, low quality",
aspectRatio: "ASPECT_1_1",
model: "V_2",
},
blogHero: {
name: "Blog Hero Image",
base: "{subject}, editorial photography, wide composition, cinematic lighting",
style: "REALISTIC",
negativePrompt: "text overlay, watermark, blurry, oversaturated",
aspectRatio: "ASPECT_16_9",
model: "V_2",
},
storyVertical: {
name: "Story / Reel",
base: "{subject}, vertical composition, eye-catching, bold colors",
style: "DESIGN",
negativePrompt: "horizontal layout, small text, blurry",
aspectRatio: "ASPECT_9_16",
model: "V_2_TURBO",
},
ogImage: {
name: "Open Graph Image",
base: '{subject}, with text "{title}" in bold clean font, tech aesthetic',
style: "DESIGN",
negativePrompt: "blurry text, misspelled words, cluttered",
aspectRatio: "ASPECT_16_9",
model: "V_2",
},
};
function buildPrompt(templateKey: string, vars: Record<string, string>): string {
const template = BRAND_TEMPLATES[templateKey];
if (!template) throw new Error(`Unknown template: ${templateKey}`);
let prompt = template.base;
for (const [key, value] of Object.entries(vars)) {
prompt = prompt.replace(`{${key}}`, value);
}
return prompt;
}
```
### Step 2: Generation Service
```typescript
import { writeFileSync, mkdirSync } from "fs";
import { join } from "path";
const API_KEY = process.env.IDEOGRAM_API_KEY!;
async function generateFromTemplate(
templateKey: string,
vars: Record<string, string>,
outputDir = "./assets"
) {
const template = BRAND_TEMPLATES[templateKey];
const prompt = buildPrompt(templateKey, vars);
const response = await fetch("https://api.ideogram.ai/generate", {
method: "POST",
headers: { "Api-Key": API_KEY, "Content-Type": "application/json" },
body: JSON.stringify({
image_request: {
prompt,
model: template.model,
style_type: template.style,
aspect_ratio: template.aspectRatio,
negative_prompt: template.negativePrompt,
magic_prompt_option: "AUTO",
},
}),
});
if (!response.ok) throw new Error(`Generate failed: ${response.status}`);
const result = await response.json();
const image = result.data[0];
// Download immediately (URLs expire ~1hr)
const imgResp = await fetch(image.url);
const buffer = Buffer.from(await imgResp.arrayBuffer());
mkdirSync(outputDir, { recursive: true });
const filename = `${templateKey}-${image.seed}.png`;
writeFileSync(join(outputDir, filename), buffer);
return {
localPath: join(outputDir, filename),
seed: image.seed,
prompt,
resolution: image.resolution,
template: templateKey,
};
}
```
### Step 3: Multi-Format Asset Pipeline
```typescript
import sharp from "sharp";
async function generateBrandAssetSet(subject: string, title: string) {
const results = [];
for (const [key, template] of Object.entries(BRAND_TEMPLATES)) {
const asset = await generateFromTemplate(key, { subject, title });
results.push(asset);
// Generate WebP variant for web
await sharp(asset.localPath)
.webp({ quality: 85 })
.toFile(asset.localPath.replace(".png", ".webp"));
// Rate limit courtesy
await new Promise(r => setTimeout(r, 3000));
}
// Generate manifest for asset tracking
const manifest = results.map(r => ({
template: r.template,
seed: r.seed,
prompt: r.prompt,
files: {
png: r.localPath,
webp: r.localPath.replace(".png", ".webp"),
},
}));
writeFileSync("./assets/manifest.json", JSON.stringify(manifest, null, 2));
console.log(`Generated ${results.length} brand assets with manifest`);
return results;
}
```
### Step 4: Describe-then-Remix Pipeline
```typescript
// Use Describe to analyze a reference image, then Remix to create variations
async function referenceBasedGeneration(referenceImagePath: string, modifications: string) {
// Step 1: Describe the reference image
const form1 = new FormData();
form1.append("image_file", new Blob([readFileSync(referenceImagePath)]));
form1.append("describe_model_version", "V_3");
const descResp = await fetch("https://api.ideogram.ai/describe", {
method: "POST",
headers: { "Api-Key": API_KEY },
body: form1,
});
const descriptions = await descResp.json();
const basePrompt = descriptions.descriptions[0].text;
// Step 2: Remix with modifications
const form2 = new FormData();
form2.append("image", new Blob([readFileSync(referenceImagePath)]));
form2.append("prompt", `${basePrompt}, ${modifications}`);
form2.append("image_weight", "40");
form2.append("rendering_speed", "DEFAULT");
const remixResp = await fetch("https://api.ideogram.ai/v1/ideogram-v3/remix", {
method: "POST",
headers: { "Api-Key": API_KEY },
body: form2,
});
return remixResp.json();
}
```
## Project Structure
```
project/
├── src/
│ ├── ideogram/
│ │ ├── client.ts # API wrapper
│ │ ├── templates.ts # Prompt templates
│ │ ├── pipeline.ts # Generation pipeline
│ │ └── types.ts # TypeScript types
│ ├── storage/
│ │ └── s3.ts # Image upload to S3/GCS
│ └── api/
│ └── generate.ts # API route handler
├── assets/ # Generated image output
│ └── manifest.json # Asset tracking
├── tests/
│ ├── templates.test.ts # Prompt template tests
│ └── pipeline.test.ts # Pipeline tests (mocked)
└── config/
├── ideogram.ts # API configuration
└── templates.json # Prompt templates (optional)
```
## Error Handling
| Issue | Cause | Solution |
|-------|-------|----------|
| Inconsistent style | No template system | Use branded prompt templates |
| URL expired | Late download | Download in same function call |
| Text misspelled | Prompt too vague | Use `DESIGN` style, quote exact text |
| Wrong aspect ratio | Template mismatch | Map templates to target platforms |
## Output
- Prompt template system for brand consistency
- Generation service with auto-download
- Multi-format asset pipeline (PNG + WebP)
- Describe-then-remix pipeline for reference-based generation
- Asset manifest for tracking and reproducibility
## Resources
- [Ideogram API Reference](https://developer.ideogram.ai/api-reference)
- [Style Guide](https://docs.ideogram.ai/using-ideogram/generation-settings/style)
- [Aspect Ratios](https://docs.ideogram.ai/using-ideogram/generation-settings/aspect-ratio-and-dimensions)
## Next Steps
For multi-environment setup, see `ideogram-multi-env-setup`.Related Skills
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