ideogram-deploy-integration
Tools and configuration scripts for deploying applications that use Ideogram image generation APIs to production platforms.
Install
mkdir -p .claude/skills/ideogram-deploy-integration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5330" && unzip -o skill.zip -d .claude/skills/ideogram-deploy-integration && rm skill.zipInstalls to .claude/skills/ideogram-deploy-integration
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Deploy Ideogram integrations to Vercel, Cloud Run, and Docker platforms.Key capabilities
- →Deploy Ideogram image generation endpoints to Vercel
- →Deploy Ideogram image generation endpoints to Cloud Run
- →Deploy Ideogram image generation endpoints to Docker
- →Configure platform-specific secrets for Ideogram API keys
- →Persist generated images to cloud storage
- →Integrate CDN for serving generated images
How it works
The skill deploys Ideogram image generation endpoints to specified platforms by configuring API keys, handling function timeouts, and persisting generated images to cloud storage.
Inputs & outputs
When to use ideogram-deploy-integration
- →Configuring environment variables for Ideogram API keys in production
- →Setting up serverless API routes for image generation
- →Implementing error handling for 5-15s generation timeouts
- →Connecting cloud storage buckets for generated image persistence
About this skill
Ideogram Deploy Integration
Overview
Deploy Ideogram image generation endpoints to Vercel, Cloud Run, or Docker. Key concerns: API key security, function timeouts (generation takes 5-15s), image persistence (URLs expire), and CDN integration for serving generated images.
Prerequisites
IDEOGRAM_API_KEYconfigured- Cloud storage for generated images (S3, GCS, or R2)
- Platform CLI installed (vercel, gcloud, or docker)
Instructions
Step 1: API Endpoint (Next.js / Vercel)
// app/api/generate/route.ts
import { NextRequest, NextResponse } from "next/server";
import { S3Client, PutObjectCommand } from "@aws-sdk/client-s3";
const s3 = new S3Client({ region: process.env.AWS_REGION });
export async function POST(req: NextRequest) {
const { prompt, style, aspectRatio } = await req.json();
if (!prompt || prompt.length > 10000) {
return NextResponse.json({ error: "Invalid prompt" }, { status: 400 });
}
// Generate image via Ideogram
const response = await fetch("https://api.ideogram.ai/generate", {
method: "POST",
headers: {
"Api-Key": process.env.IDEOGRAM_API_KEY!,
"Content-Type": "application/json",
},
body: JSON.stringify({
image_request: {
prompt,
model: "V_2",
style_type: style || "AUTO",
aspect_ratio: aspectRatio || "ASPECT_1_1",
magic_prompt_option: "AUTO",
},
}),
});
if (!response.ok) {
const err = await response.text();
return NextResponse.json({ error: `Generation failed: ${response.status}` }, { status: 502 });
}
const result = await response.json();
const image = result.data[0];
// Download and persist to S3 (Ideogram URLs expire)
const imgResponse = await fetch(image.url);
const buffer = Buffer.from(await imgResponse.arrayBuffer());
const key = `generated/${image.seed}-${Date.now()}.png`;
await s3.send(new PutObjectCommand({
Bucket: process.env.S3_BUCKET!,
Key: key,
Body: buffer,
ContentType: "image/png",
}));
return NextResponse.json({
url: `https://${process.env.CDN_DOMAIN}/${key}`,
seed: image.seed,
resolution: image.resolution,
style: image.style_type,
});
}
export const maxDuration = 60; // Vercel function timeout
Step 2: Vercel Configuration
{
"functions": {
"app/api/generate/route.ts": {
"maxDuration": 60
}
},
"env": {
"IDEOGRAM_API_KEY": "@ideogram-api-key"
}
}
set -euo pipefail
# Set secrets
vercel env add IDEOGRAM_API_KEY production
vercel env add S3_BUCKET production
vercel env add CDN_DOMAIN production
Step 3: Cloud Run Deployment
FROM node:20-slim
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
RUN npm run build
EXPOSE 3000
# Cloud Run sets PORT automatically
CMD ["node", "dist/server.js"]
set -euo pipefail
# Store API key in Secret Manager
echo -n "$IDEOGRAM_API_KEY" | gcloud secrets create ideogram-api-key --data-file=-
# Deploy with secret mount
gcloud run deploy ideogram-service \
--image=gcr.io/$PROJECT_ID/ideogram-service \
--set-secrets=IDEOGRAM_API_KEY=ideogram-api-key:latest \
--timeout=120 \
--memory=512Mi \
--max-instances=10 \
--allow-unauthenticated
Step 4: Docker Compose (Self-Hosted)
# docker-compose.yml
services:
ideogram-api:
build: .
ports:
- "3000:3000"
environment:
- IDEOGRAM_API_KEY=${IDEOGRAM_API_KEY}
- S3_BUCKET=${S3_BUCKET}
- NODE_ENV=production
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:3000/health"]
interval: 30s
timeout: 10s
retries: 3
restart: unless-stopped
Step 5: Health Check Endpoint
// app/api/health/route.ts
export async function GET() {
const checks = {
ideogram: {
configured: !!process.env.IDEOGRAM_API_KEY,
keyLength: process.env.IDEOGRAM_API_KEY?.length ?? 0,
},
storage: {
configured: !!process.env.S3_BUCKET,
},
};
const healthy = checks.ideogram.configured && checks.storage.configured;
return Response.json({
status: healthy ? "healthy" : "degraded",
checks,
}, { status: healthy ? 200 : 503 });
}
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Function timeout | Generation takes 5-15s | Set timeout to 60s+ |
| Content filtered | Prompt policy violation | Return 422 with user-friendly message |
| Storage upload fails | Bad credentials | Verify S3/GCS permissions |
| Rate limited | Too many concurrent users | Queue generation jobs with BullMQ |
| Expired URL | Late download | Download immediately in same request |
Output
- Deployed API endpoint with image generation
- Images persisted to durable storage with CDN URLs
- Health check endpoint for monitoring
- Platform-specific configuration files
Resources
Next Steps
For event-driven patterns, see ideogram-webhooks-events.
When not to use it
- →When the Ideogram API key is not configured
- →When cloud storage for generated images is not available
- →When the platform CLI is not installed
Prerequisites
Limitations
- →Function timeouts can occur if image generation exceeds 60 seconds
- →Content filtered by Ideogram's policy will result in a 422 error
- →Storage upload failures can occur due to incorrect cloud credentials
How it compares
This skill automates the deployment and configuration of Ideogram integrations, unlike manual processes that require individual setup of API keys, storage, and platform-specific settings.
Compared to similar skills
ideogram-deploy-integration side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| ideogram-deploy-integration (this skill) | 1 | 27d | Caution | Intermediate |
| deployment-pipeline-design | 6 | 2mo | Review | Advanced |
| vercel-deployment | 3 | 6mo | No flags | Intermediate |
| ecs | 2 | 3mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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