Build AI Avatar generation Web App using NextJs

Follow a road map to build a Next.js web app with authentication, Stripe payments, S3 uploads, and a Dreambooth training workflow via Replicate.

Build a landing page with full-height, full-width layout, a header, gradient styling, and a button to open the authentication dialog for login.

Build a reusable authentication modal in a Next.js app by composing a dialog with header, content, and footer, including an email input and sign in with Google option.

Implement Google OAuth and email authentication in a Next.js app using NextAuth and Google Cloud credentials. Deploy PlanetScale serverless DB and sync Prisma schema for scalable data storage.

Explore implementing Stripe payments in a Next.js app by creating a checkout session, using a webhook to update the database on payment success, and managing products and env vars.

This lecture shows setting up Stripe in a Next.js app, initializing Stripe with env keys and the latest API version, and creating a checkout session to redirect to Stripe checkout.

Build a Stripe webhook in a Next.js app to process payment events and update your database via Prisma upsert, with signature verification and security checks.

Develop an ai avatar web app with next.js by implementing an s3-backed image upload using a react dropzone, showing previews, validating 3–10 png/jpg files, and securing a dashboard behind payment.

Learn how to upload images to aws s3 from a next.js app by generating signed upload URLs, configuring a bucket and permissions, and handling client-side uploads securely.

Show the user’s uploaded images on the dashboard by listing S3 objects under the user’s folder, generating signed URLs, and rendering them alongside the dropzone upload flow.

Builds a delete image from S3 workflow within a NextJs ai avatar app, mapping image keys and signed URLs, executing a protected mutation, handling per-image loading, and refreshing the dashboard.

Resize images in the browser before uploading to S3, using image blob reduce, crop, and zip workflows to enable rapid model training via Replicate API while managing timeout constraints.

Crop and zip images to 512 by 512 using smart crop and sharp, then upload the zip to S3, and trigger backend image processing for model training.

Train an ai avatar model from user uploaded images by zipping uploads to s3, retrieving with a signed url, and initiating training via replicate's dreambooth api.

Learn to build an ai avatar generation app by wiring prompts to the replicate api, manage credits and a unique keyword, and implement a clean prompt input for avatar generation.

Learn how to save generated image URLs to a user-specific images table via a webhook, wire up Prisma models, and trigger emails and credit updates during avatar generation.