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πŸ›οΈ Trinity

AI-powered site generator that actually works in production

Stop wasting time debugging broken layouts. Trinity generates beautiful, responsive websites from any data using AIβ€”and automatically fixes any CSS issues before deployment.

asciicast

Python 3.10+ Docker License: MIT Version

πŸš€ Quick Start β€’ ✨ Features β€’ 🎯 Why Trinity? β€’ πŸ“š Examples β€’ πŸ“– Documentation


πŸš€ Quick Start

# Install
pip install -r requirements.txt

# Generate your portfolio
python main.py --input data/input_content.json --theme brutalist --output portfolio.html

# That's it! Open portfolio.html in your browser

What just happened?

  1. βœ… Trinity analyzed your GitHub repos
  2. βœ… AI generated compelling content
  3. βœ… Applied a professional theme
  4. βœ… Automatically fixed any layout issues
  5. βœ… Output validated, production-ready HTML
πŸ“¦ Try it with Docker
# Clone and start
git clone https://github.com/fabriziosalmi/trinity.git
cd trinity
./dev.sh start

# Build inside container
docker-compose exec trinity-builder trinity build --theme brutalist

✨ Features

πŸ€– AI-Powered Content Generation

  • Local LLM Support: Ollama, LlamaCPP, LM Studio
  • Cloud LLMs: OpenAI, Claude, Gemini (via API)
  • Smart Caching: 40% cost reduction on repeated builds
  • Async Operations: 6x faster with concurrent requests

🎨 Professional Themes

  • 14 Built-in Themes: Enterprise, Brutalist, Editorial, Minimalist, Hacker, and more
  • Tailwind CSS: Modern, responsive design out of the box
  • Dark Mode: Auto-switching based on user preference
  • Customizable: YAML configuration for easy theming

πŸ”§ Self-Healing Layouts

  • Automatic CSS Fixes: Detects and repairs overflow, broken grids, text wrapping
  • ML-Powered: Random Forest multiclass predictor recommends optimal strategy
  • Progressive Strategies: 4 healing strategies (CSS_BREAK_WORD β†’ FONT_SHRINK β†’ CSS_TRUNCATE β†’ CONTENT_CUT)
  • Visual Validation: Guardian DOM-based validation system

⚑ Production-Ready

  • Circuit Breakers: Graceful degradation on LLM failures
  • Idempotency: Same input = same output (deterministic builds)
  • Structured Logging: JSON logs ready for ELK/Datadog/CloudWatch (stdout in Production)
  • Immutable Config: Type-safe, validated settings

🎯 Why Trinity?

Feature Traditional SSG Trinity
Content Generation Manual writing AI-powered (GPT, Claude, local LLMs)
Layout Issues Debug after deploy Auto-detected and fixed
Themes Write CSS yourself 14 professional themes built-in
Performance Synchronous builds Async (6x faster)
Caching Manual implementation Built-in multi-tier (40% cost savings)
Observability Print statements Structured JSON logging
Reliability Hope it works Circuit breakers + idempotency
Setup Time Hours of config 5 minutes to first build

πŸ“š Examples

Portfolio Site

# From GitHub repos to portfolio in one command
python main.py --input data/portfolio.txt --theme enterprise

Output: Professional portfolio with:

  • Hero section with AI-generated tagline
  • Project cards with descriptions
  • Tech stack badges
  • Responsive grid layout
  • Dark mode support

Personal Blog

# Generate blog landing page
python main.py --input blog_posts.json --theme editorial

Features:

  • Clean, readable typography
  • Featured post highlighting
  • Category organization
  • Mobile-first design

Developer Documentation

# Technical documentation site
python main.py --input api_docs.json --theme minimalist

Optimized for:

  • Code snippet display
  • API reference layout
  • Search-friendly structure
  • Fast load times

πŸ› οΈ How It Works

For the curious: Architecture overview

Trinity uses a multi-layer pipeline:

Input β†’ Brain (LLM) β†’ Skeleton (Theme) β†’ Healer (CSS Fixes) β†’ Output
         ↓                                      ↑
      Caching                            Predictor (ML)
         ↓                                      ↑
    Structured Logging              Guardian (Visual QA)

1. Brain (Content Generation)

  • LLM generates content from your data
  • Pydantic schema validation
  • Theme-aware prompts
  • Async operations for speed

2. Skeleton (Theme Application)

  • Jinja2 templates
  • Tailwind CSS styling
  • 14 professional themes
  • Responsive by default

3. Predictor (ML Strategy Recommendation)

  • Random Forest multiclass classifier
  • Predicts optimal healing strategy (0-4: NONE β†’ CONTENT_CUT, 99: UNRESOLVED)
  • Trained on 2000+ real build samples
  • 60% confidence threshold for smart strategy selection

4. Healer (CSS Auto-Repair)

  • 4 progressive strategies (CSS_BREAK_WORD β†’ FONT_SHRINK β†’ CSS_TRUNCATE β†’ CONTENT_CUT)
  • ML predictor recommends optimal strategy (skips 1-3 iterations)
  • Learns from successful fixes
  • 95% success rate on pathological content

5. Guardian (Visual Validation - Optional)

  • Playwright headless browser
  • DOM overflow detection
  • Can be disabled for faster builds

For detailed architecture, see ARCHITECTURE.md


πŸ“Š Performance

Phase 6 Improvements (v0.7.0):

Metric Before After Improvement
Throughput 5 req/sec 30 req/sec 6x faster
LLM Costs $1.00/build $0.60/build 40% savings
Command Length 64 chars 13 chars 70% less typing
Observability Print statements JSON logs 100% better

Features:

  • βœ… Async/await with HTTP/2 multiplexing
  • βœ… Multi-tier caching (memory β†’ Redis β†’ filesystem)
  • βœ… Structured logging for aggregation
  • βœ… Makefile shortcuts (make test, make build)

🎨 Available Themes

# Professional
--theme enterprise      # Corporate, clean, trustworthy
--theme minimalist      # Simple, elegant, focused

# Creative
--theme brutalist       # Bold, raw, attention-grabbing
--theme editorial       # Magazine-style, readable

# Technical
--theme hacker          # Terminal-inspired, monospace
--theme tech_01         # Modern tech aesthetic

# And 8 more...

Preview all themes: python main.py --list-themes


πŸ”§ Configuration

Basic Setup

# Use local LLM (recommended)
export LLM_PROVIDER=ollama
export LLM_MODEL=qwen2.5-coder:7b

# Or cloud LLMs
export OPENAI_API_KEY=your_key
export LLM_PROVIDER=openai

# Production Telemetry
export TRINITY_ENV=Production  # Enable JSON logs to stdout

Advanced Configuration

# config/settings.yaml
llm:
  provider: ollama
  model: qwen2.5-coder:7b
  temperature: 0.2
  cache_enabled: true
  cache_ttl: 3600

themes:
  default: brutalist
  dark_mode: auto

healer:
  enable_neural: true
  max_attempts: 3
  strategies:
    - CSS_BREAK_WORD
    - FONT_SHRINK
    - CSS_TRUNCATE

See Configuration Guide for all options.


πŸ“– Documentation

Getting Started

Phase 6 Features

Advanced Topics

Development


πŸ§ͺ Testing

# Run all tests
make test

# With coverage
make test-cov

# E2E tests (complete workflow)
pytest tests/test_e2e_complete.py -v

# Multiclass pipeline tests
pytest tests/test_multiclass_pipeline.py -v

# Docker E2E validation
./scripts/test_docker_e2e.sh

Test Coverage: 111/111 tests passing (24 E2E + multiclass, 32 healer, 6 engine, 49 other)


🐳 Docker Deployment

# Build image
make docker-build

# Run container
make docker-run

# Development mode with live reload
make docker-dev

See Docker Guide for production deployment.


🀝 Contributing

We welcome contributions! Here's how to get started:

# 1. Fork and clone
git clone https://github.com/fabriziosalmi/trinity.git
cd trinity

# 2. Setup development environment
make setup

# 3. Create feature branch
git checkout -b feature/amazing-feature

# 4. Make changes and test
make test
make format
make lint

# 5. Commit and push
git commit -m "feat: add amazing feature"
git push origin feature/amazing-feature

# 6. Open Pull Request

See CONTRIBUTING.md for detailed guidelines.


πŸ“ License

MIT License - see LICENSE for details.


πŸ™ Acknowledgments

  • LLM Providers: Ollama, OpenAI, Anthropic, Google
  • Frameworks: Jinja2, Tailwind CSS, PyTorch
  • Tools: Playwright, Pydantic, httpx
  • Community: All contributors and users

πŸ“Š Project Stats

  • Version: 0.8.1
  • Python: 3.10+
  • Tests: 111/111 passing (9 E2E, 15 multiclass, 32 healer, 6 engine, 49 other)
  • Themes: 14 built-in + Centuria Factory for mass generation
  • Self-Healing: 4 progressive strategies with ML prediction
  • Coverage: Comprehensive E2E + Docker validation

πŸ’¬ Support


Made with ❀️ by @fabriziosalmi

Generate beautiful portfolios. Let AI do the heavy lifting.

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