ID

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.zip

Installs 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.
72 charsno explicit “when” trigger
Intermediate

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

You give it
Ideogram-powered application code and deployment configuration
You get back
Deployed API endpoint with image generation, persisted images, and a health check endpoint

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_KEY configured
  • 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

IssueCauseSolution
Function timeoutGeneration takes 5-15sSet timeout to 60s+
Content filteredPrompt policy violationReturn 422 with user-friendly message
Storage upload failsBad credentialsVerify S3/GCS permissions
Rate limitedToo many concurrent usersQueue generation jobs with BullMQ
Expired URLLate downloadDownload 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

IDEOGRAM_API_KEY configuredCloud storage for generated images (S3, GCS, or R2)Platform CLI installed (vercel, gcloud, or docker)

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.

SkillInstallsUpdatedSafetyDifficulty
ideogram-deploy-integration (this skill)127dCautionIntermediate
deployment-pipeline-design62moReviewAdvanced
vercel-deployment36moNo flagsIntermediate
ecs23moReviewIntermediate

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