Ideogram Events & Async Patterns

Overview

Ideogram's API is synchronous -- each call blocks until the image is generated (5-15 seconds). For production applications, wrap it in async patterns: job queues for batch generation, callbacks for downstream processing, and pipelines for image post-processing. This skill covers BullMQ queue patterns, callback handlers, and asset processing pipelines.

Prerequisites

• IDEOGRAM_API_KEY

  configured
• Redis for BullMQ job queue
• Storage for generated images (S3, GCS, or R2)
• Understanding of Ideogram models and style types

Instructions

Step 1: Job Queue for Async Generation

import { Queue, Worker } from "bullmq";
import { writeFileSync, mkdirSync } from "fs";
import { join } from "path";

interface GenerationJob {
  prompt: string;
  style: string;
  aspectRatio: string;
  model: string;
  callbackUrl?: string;
  metadata?: Record<string, string>;
}

const connection = { host: "localhost", port: 6379 };
const imageQueue = new Queue("ideogram-generation", { connection });

// Enqueue a generation job
async function submitGeneration(job: GenerationJob) {
  return imageQueue.add("generate", job, {
    attempts: 3,
    backoff: { type: "exponential", delay: 2000 },
    removeOnComplete: 100,
    removeOnFail: 50,
  });
}

// Worker processes jobs with concurrency limit
const worker = new Worker("ideogram-generation", async (job) => {
  const { prompt, style, aspectRatio, model, callbackUrl, metadata } = job.data;

  // Call Ideogram API (synchronous, blocks 5-15s)
  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: model || "V_2",
        style_type: style || "AUTO",
        aspect_ratio: aspectRatio || "ASPECT_1_1",
        magic_prompt_option: "AUTO",
      },
    }),
  });

  if (response.status === 429) {
    throw new Error("Rate limited"); // BullMQ will retry with backoff
  }
  if (!response.ok) {
    throw new Error(`Ideogram API error: ${response.status}`);
  }

  const result = await response.json();
  const image = result.data[0];

  // Download immediately (URLs expire)
  const imgResp = await fetch(image.url);
  const buffer = Buffer.from(await imgResp.arrayBuffer());
  const outputDir = "./generated";
  mkdirSync(outputDir, { recursive: true });
  const filePath = join(outputDir, `${image.seed}.png`);
  writeFileSync(filePath, buffer);

  // Fire callback if provided
  if (callbackUrl) {
    await fetch(callbackUrl, {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify({
        event: "generation.completed",
        jobId: job.id,
        prompt,
        seed: image.seed,
        resolution: image.resolution,
        filePath,
        metadata,
      }),
    });
  }

  return { seed: image.seed, filePath, resolution: image.resolution };
}, {
  connection,
  concurrency: 5, // Stay under 10 in-flight limit
});

worker.on("failed", (job, err) => {
  console.error(`Job ${job?.id} failed:`, err.message);
});

Step 2: Callback Handler

import express from "express";

const app = express();
app.use(express.json());

app.post("/callbacks/ideogram", async (req, res) => {
  const { event, jobId, seed, filePath, metadata } = req.body;
  res.status(200).json({ received: true });

  switch (event) {
    case "generation.completed":
      console.log(`Image generated: seed=${seed}, path=${filePath}`);
      await processImage(filePath, metadata);
      break;
    case "generation.failed":
      console.error(`Generation failed: job=${jobId}`);
      await notifyFailure(jobId, req.body.error);
      break;
  }
});

Step 3: Batch Marketing Asset Generation

async function generateMarketingCampaign(
  campaignName: string,
  products: string[],
  formats: Array<{ name: string; aspect: string; style: string }>
) {
  const jobs = [];

  for (const product of products) {
    for (const format of formats) {
      const job = await submitGeneration({
        prompt: `${product}, professional ${format.name} design, high quality`,
        style: format.style,
        aspectRatio: format.aspect,
        model: "V_2",
        callbackUrl: "https://api.myapp.com/callbacks/ideogram",
        metadata: { campaign: campaignName, product, format: format.name },
      });
      jobs.push(job);
    }
  }

  console.log(`Submitted ${jobs.length} generation jobs for campaign: ${campaignName}`);
  return jobs.map(j => j.id);
}

// Example: Generate all assets for a product launch
await generateMarketingCampaign("Q1 Launch", [
  "Cloud analytics dashboard",
  "Mobile payment app",
], [
  { name: "social-square", aspect: "ASPECT_1_1", style: "DESIGN" },
  { name: "story-vertical", aspect: "ASPECT_9_16", style: "DESIGN" },
  { name: "blog-hero", aspect: "ASPECT_16_9", style: "REALISTIC" },
]);

Step 4: Image Post-Processing Pipeline

import sharp from "sharp";

async function processImage(filePath: string, metadata?: Record<string, string>) {
  const variants = [
    { suffix: "-og", width: 1200, height: 630 },       // Open Graph
    { suffix: "-thumb", width: 400, height: 400 },      // Thumbnail
    { suffix: "-social", width: 1080, height: 1080 },   // Instagram
  ];

  for (const variant of variants) {
    const outputPath = filePath.replace(".png", `${variant.suffix}.webp`);
    await sharp(filePath)
      .resize(variant.width, variant.height, { fit: "cover" })
      .webp({ quality: 85 })
      .toFile(outputPath);
    console.log(`Created variant: ${outputPath}`);
  }
}

Error Handling

Issue	Cause	Solution
Rate limited	Too many concurrent jobs	Set worker concurrency to 5
Content filtered	Prompt violates policy	Log and skip, notify reviewer
Expired URL	Worker too slow	Download in same worker step
Queue stalled	Redis connection lost	Configure BullMQ connection retry
Callback fails	Downstream service down	Fire-and-forget with retry queue

Output

• BullMQ job queue for async generation
• Callback handler for downstream processing
• Batch generation for marketing campaigns
• Post-processing pipeline with sharp

Resources

• Ideogram API Reference
• BullMQ Documentation
• sharp Image Processing

Next Steps

For performance optimization, see

ideogram-performance-tuning

.