How to vibe codeDreamStudio

Prerequisites

• Node.jsfree

  Required runtime for building and running the Next.js full-stack web application.

• GitHubfree

  Source control and deployment pipeline bridge for Vercel hosting.

• 

  fal.ai API AccountPay-as-you-go (~$0.003/image)

  Provides fast serverless inference endpoints for Stable Diffusion and image upscaling without managing raw GPUs.

AI coding tools

• Claude Code

  Best-in-class terminal agent for scaffolding the full-stack Next.js application, database schema, and API integrations in multi-step loops.

• Cursor

  Ideal for fine-tuning complex client-side canvas components and interactive UI state transitions.

Build guide

1. 01Scaffold Next.js App and Database Schema

   Initialize the Next.js project with Tailwind CSS, configure Turso SQLite via Drizzle ORM, and set up better-auth for personal user session management.

   Create a new Next.js App Router project configured with TypeScript and Tailwind CSS. Initialize Turso SQLite database connectivity using Drizzle ORM with tables for users, credit_balances, and generations (storing prompt, negative_prompt, image_url, model, width, height, steps, and created_at). Integrate better-auth for simple email/password user authentication. Ensure all configuration files, environment variable validators, and layout wrappers are completely written out without placeholders.

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2. 02Build the Generation Dashboard Layout

   Create a split-pane workspace dashboard featuring a sidebar for prompt inputs, parameter sliders (steps, guidance scale, dimensions), and a main canvas viewport.

   Build a responsive web app layout using Tailwind CSS inside Next.js. The interface should feature a collapsible left-hand sidebar for parameter controls (text prompt textarea, negative prompt, aspect ratio selector, inference steps slider, guidance scale slider, and model picker) and a large central workspace area designed to display generated images or interactive canvas tools. Include a top navigation bar showing user credit balance and account profile status.

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3. 03Integrate fal.ai Serverless Inference API

   Implement server actions to communicate with the fal.ai API for running text-to-image generations and handling asynchronous image return payloads.

   Implement a Next.js Server Action that accepts prompt parameters, validates user credit balance, and calls the fal.ai Stable Diffusion / Flux inference API endpoint securely using server-side environment variables. Handle asynchronous response handling, download or link the resulting image output, deduct credits from the user's Turso database balance, and save the generation record to the database history table.

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4. 04Build Canvas Inpainting and Outpainting Editor

   Develop an HTML5 canvas layer that allows users to paint mask overlays for inpainting transformations alongside image cropping and basic viewing utilities.

   Build an interactive HTML5 canvas component in React that supports loading an existing generated image, selecting brush sizes, and painting mask strokes directly onto the canvas for inpainting workflows. Export the resulting mask layer as a base64 string alongside the source image, and pass both payloads to a new server action that invokes fal.ai's inpainting pipeline. Include clear undo/redo state management for brush edits.

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5. 05Implement Generation History and Gallery

   Create a history view and sidebar gallery where users can browse, inspect, favorite, and reload previous generations and prompts into the main workspace.

   Create a history gallery component that fetches past generations from the Turso database for the authenticated user in a grid layout with pagination or infinite scroll. Clicking an item in the gallery should open a detail modal or load its parameters directly back into the generation sidebar controls and workspace canvas for iterative tweaking. Add a favorites toggle and delete action.

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6. 06Polish UI States, Error Handling, and Deployment

   Add loading skeletons, error boundaries, toast notifications for API failures, and configure the project for deployment on Vercel.

   Add robust error handling and loading indicators across all async workflows, including skeleton loaders on the canvas during image generation and toast notifications for credit shortages or API errors. Verify that all environment variables are properly documented in a .env.example file and write instructions for deploying the project to Vercel connected to Turso.

   ⧉copy promptopen in Claude CodeCopen in Codexopen in Cursor

Cost vs paying for DreamStudio