🎨 Image Generation with Replicate

This template uses the Replicate API to run image generation models like Stable Diffusion XL (SDXL), allowing users to generate images based on a text prompt.

How it Works

The process involves making API calls to Replicate's /predictions endpoint. Here's a short breakdown:

  1. Submit a Prediction Request

    • The frontend initiates the image generation by sending a POST request to the /api/replicate NextJS API route. This request includes a payload with the user's prompt.
    • The API route passes this request off to Replicate's /predictions API endpoint.
  2. Check Prediction Status

    • After the initial request, the frontend keeps checking the status of the prediction by sending GET requests to /api/replicate/[prediction_id]. While the prediction is ongoing, the app displays a loading spinner.
  3. Handling Success or Failure

    • Once the prediction is completed, the app updates the UI. If the prediction is successful, the generated image is displayed to the user.
  4. Uploading to Supabase

    • If the prediction is successful, its details are stored in Supabase in the sdxl_images table. This includes a URL to the image stored on Replicate's database. (Note that Replicate automatically deletes generated images in a few hours, so you need to store them separately in Supabase storage to make them persistent.)

3-Min Walkthrough

Steps taken on the frontend

1. Making a Prediction Request

To generate an image, users enter a prompt on the /dashboard/generate page. The app then sends this prompt to Replicate for processing.

// Example of submitting a prediction request
const handleSubmit = async (e: any) => {
  const response = await fetch('/api/replicate', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
    body: JSON.stringify({
      input: {
        prompt: e.target.prompt.value,
  // Handling response...

2. Checking Prediction Status

The app continuously checks the status of the prediction until it's either succeeded or failed.

// Example of checking prediction status
while (prediction.status !== 'succeeded' && prediction.status !== 'failed') {
  await sleep(1000);
  const response = await fetch('/api/replicate/' + prediction.id);
  prediction = await response.json();
  // Handling response...

3. Uploading to Supabase

If the prediction is successful, the generated image is uploaded to Supabase.

// Example of uploading generated image to Supabase
if (prediction.status === 'succeeded') {
  await uploadGeneratedImage(prediction);


Configure the following in your app to start using image generation:

1. Replicate API Token

Go to your Replicate Account, copy the API Token, and set it in your .env file.

# Update this with your Replicate API Key

2. Model and Version

Specify the Replicate model and version you want to run in your environment. By default, the .env.example pins this to a version of Stable Diffusion:

# Update this with the model and version you want to run

You can find the version for any model on the Versions tab of the model card on Replicate's website (https://replicate.com/[company]/[model]/versions).

Replicate Version

Last Updated: March 5