Prompt: rewrite as a neanderthal caveman — broken grammar, grunt words (ugh, oog), simplest names (big rock, fire stick), dropped articles and conjugations, thoughts about food/shelter/danger, raw emotional outbursts.
English Style Converter
A SvelteKit web app that converts English text into various styles and tones using an LLM.
Quick Start (Docker)
# Option 1: Use default model (llama3)
docker compose up
# Option 2: Choose a different model
OLLAMA_MODEL=gemma2 docker compose up
- App: http://localhost:3000
- Ollama API: http://localhost:11434
First startup pulls the model from Ollama, which may take a few minutes depending on model size and your connection. Subsequent starts are instant (model is cached in a Docker volume).
To change the model later, edit .env.docker and run:
docker compose down
docker compose up --build
Local Development (without Docker)
Prerequisites: Ollama running locally with a model pulled.
# Install dependencies
npm install
# Copy env config (defaults to Ollama at localhost:11434)
cp .env.example .env
# Start dev server
npm run dev
Configuration
| Variable | Default | Description |
|---|---|---|
OPENAI_BASE_URL |
http://localhost:11434/v1 |
OpenAI-compatible API endpoint |
OPENAI_API_KEY |
ollama |
API key (use ollama for local Ollama) |
OPENAI_MODEL |
llama3 |
Model to use |
PORT |
3000 |
App port (Docker/adapter-node only) |
For Docker, set OLLAMA_MODEL in .env.docker — it controls both the model Ollama pulls and the model the app requests.
Styles
6 categories, 25 styles: Sarcastic, Formal, British (Polite, Formal, Witty, Gentlemanly, Upper Class, Royal, Victorian, Downton Abbey), American (New Yorker, AAVE, Southern, Redneck), Pirate, Shakespearean, Gen Z, Game of Thrones (King's Landing, Wildlings, Winterfell), and Newspeak (Orwellian).
Testing
npm test