Convert screenshots to code using AI

Nov 29, 2024

https://screenshottocode.com/https://github.com/abi/screenshot-to-code

A simple tool to convert screenshots, mockups and Figma designs into clean, functional code using AI. Now supporting Claude Sonnet 3.5 and GPT-4o!

Supported stacks:

HTML + Tailwind
HTML + CSS
React + Tailwind
Vue + Tailwind
Bootstrap
Ionic + Tailwind
SVG

Supported AI models:

Claude Sonnet 3.5 - Best model!
GPT-4o - also recommended!
DALL-E 3 or Flux Schnell (using Replicate) for image generation

Also with experimental support for taking a video/screen recording of a website in action and turning that into a functional prototype.

Hosted version

Try it live on the hosted version (paid). If you're a large or medium enterprise (50+ employees), book a meeting to explore custom enterprise plans.

Self deploy

The app has a React/Vite frontend and a FastAPI backend.

Keys needed:

OpenAI API key with access to GPT-4 or Anthropic key (optional)
Both are recommended so you can compare results from both Claude and GPT4o

If you'd like to run the app with Ollama open source models (not recommended due to poor quality results), follow this comment.

Run the backend (I use Poetry for package management - pip install poetry if you don't have it):

cd backend
echo "OPENAI_API_KEY=sk-your-key" > .env
echo "ANTHROPIC_API_KEY=your-key" > .env
poetry install
poetry shell
poetry run uvicorn main:app --reload --port 7001

You can also set up the keys using the settings dialog on the front-end (click the gear icon after loading the frontend).

Run the frontend:

cd frontend
yarn
yarn dev

Open http://localhost:5173 to use the app.

If you prefer to run the backend on a different port, update VITE_WS_BACKEND_URL in frontend/.env.local

For debugging purposes, if you don't want to waste GPT4-Vision credits, you can run the backend in mock mode (which streams a pre-recorded response):

MOCK=true poetry run uvicorn main:app --reload --port 7001

Docker

If you have Docker installed on your system, in the root directory, run:

echo "OPENAI_API_KEY=sk-your-key" > .env
docker-compose up -d --build

The app will be up and running at http://localhost:5173. Note that you can't develop the application with this setup as the file changes won't trigger a rebuild.