ideogram-webhooks-events

Ideogram Events & Async Patterns

Overview

Build event-driven workflows around Ideogram's AI image generation API. Ideogram's api.ideogram.ai endpoints handle text-to-image and image editing requests.

Prerequisites

• Ideogram API key stored in IDEOGRAM_API_KEY environment variable
• Storage solution for generated images (S3, GCS, Cloudflare R2)
• Queue system for batch image generation
• Understanding of Ideogram models (V_2, V_2_TURBO)

Event Patterns

Pattern	Trigger	Use Case
Generation callback	Image generation completes	Asset pipeline processing
Batch generation	Multiple prompts queued	Marketing asset creation
Image ready notification	Post-processing done	CDN upload and cache warming
Generation failure alert	API error or content filter	Retry or manual review

Instructions

Step 1: Async Image Generation with Callbacks

import { Queue, Worker } from "bullmq";

interface GenerationJob {
  prompt: string;
  style: "REALISTIC" | "DESIGN" | "RENDER_3D" | "ANIME";
  aspectRatio: "ASPECT_1_1" | "ASPECT_16_9" | "ASPECT_9_16";
  callbackUrl?: string;
  model: "V_2" | "V_2_TURBO";
}

const imageQueue = new Queue("ideogram-generation");

async function queueGeneration(job: GenerationJob) {
  return imageQueue.add("generate", job, {
    attempts: 3,
    backoff: { type: "exponential", delay: 2000 },  # 2000: 2 seconds in ms
  });
}

const worker = new Worker("ideogram-generation", async (job) => {
  const { prompt, style, aspectRatio, model, callbackUrl } = job.data;

  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,
        style_type: style,
        aspect_ratio: aspectRatio,
        magic_prompt_option: "AUTO",
      },
    }),
  });

  const result = await response.json();
  const images = result.data;

  // Upload generated images to storage
  const uploadedUrls = [];
  for (const image of images) {
    const url = await uploadToStorage(image.url, `generated/${job.id}`);
    uploadedUrls.push(url);
  }

  // Fire callback
  if (callbackUrl) {
    await fetch(callbackUrl, {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify({
        event: "ideogram.generation.completed",
        jobId: job.id,
        prompt,
        images: uploadedUrls,
        resolution: images[0]?.resolution,
      }),
    });
  }

  return { images: uploadedUrls };
});

Step 2: Handle Generation Events

app.post("/webhooks/ideogram-callback", async (req, res) => {
  const { event, jobId, images, prompt } = req.body;
  res.status(200).json({ received: true });  # HTTP 200 OK

  switch (event) {
    case "ideogram.generation.completed":
      console.log(`Generated ${images.length} images for: "${prompt}"`);
      await processGeneratedImages(jobId, images);
      break;
    case "ideogram.generation.failed":
      console.error(`Generation failed for job ${jobId}`);
      await handleGenerationFailure(jobId, req.body.error);
      break;
  }
});

Step 3: Batch Marketing Asset Generation

async function generateMarketingAssets(campaign: string, prompts: string[]) {
  const jobs = prompts.map(prompt =>
    queueGeneration({
      prompt,
      style: "DESIGN",
      aspectRatio: "ASPECT_16_9",
      model: "V_2",
      callbackUrl: `https://api.myapp.com/webhooks/ideogram-callback`,
    })
  );

  const results = await Promise.all(jobs);
  return results.map(j => j.id);
}

Step 4: Image Post-Processing Pipeline

async function processGeneratedImages(jobId: string, imageUrls: string[]) {
  for (const url of imageUrls) {
    // Resize for different platforms
    await imageProcessor.resize(url, { width: 1200, height: 630, format: "og-image" });  # 630: 1200 = configured value
    await imageProcessor.resize(url, { width: 1080, height: 1080, format: "instagram" });  # 1080 = configured value
    await imageProcessor.resize(url, { width: 1500, height: 500, format: "twitter-header" });  # 1500: HTTP 500 Internal Server Error
  }
}

Error Handling

Issue	Cause	Solution
Content filtered	Prompt violates policy	Revise prompt, check content guidelines
Rate limited	Too many requests	Queue jobs with concurrency limits
Low quality output	Vague prompt	Add style details and negative prompts
Timeout	Large batch	Process sequentially with delays

Examples

Quick Single Generation

set -euo pipefail
curl -X POST https://api.ideogram.ai/generate \
  -H "Api-Key: $IDEOGRAM_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"image_request": {"prompt": "Modern logo for tech startup", "model": "V_2", "style_type": "DESIGN"}}'

Resources

• Ideogram API Documentation
• Ideogram Style Guide

Next Steps

For deployment setup, see ideogram-deploy-integration.

Output

• Configuration files or code changes applied to the project
• Validation report confirming correct implementation
• Summary of changes made and their rationale