inceptor 0.1.1

Multi-Level Solution Architecture Generator powered by Ollama Mistral:7b

🌀 Inceptor

AI-Powered Multi-Level Solution Architecture Generator

Inceptor is a powerful AI-powered tool that helps you design, generate, and implement complex software architectures using natural language. Built with Ollama's Mistral:7b model, it creates multi-level architecture designs that evolve from high-level concepts to detailed implementation plans.

✨ Key Features

• 🤖 AI-Powered: Leverages Ollama's Mistral:7b for intelligent architecture generation
• 🏗️ Multi-Level Design: Creates 5 distinct architecture levels (LIMBO → DREAM → REALITY → DEEPER → DEEPEST)
• 🔍 Context-Aware: Understands requirements from natural language descriptions
• 💻 Interactive CLI: Command-line interface with autocomplete and suggestions
• 📊 Structured Output: Exports to Markdown, JSON, YAML, and more
• 🚀 Zero-Setup: Works out of the box with local Ollama installation
• 🔌 Extensible: Plugin system for custom generators and templates

🚀 Quick Start

Prerequisites

• Python 3.8 or higher
• Ollama with Mistral:7b model
• 4GB RAM (minimum)

Installation

# Install from PyPI
pip install inceptor

# Or install from source
git clone https://github.com/wronai/inceptor.git
cd inceptor
make install  # Installs in development mode with all dependencies

Basic Usage

# Generate architecture from a description
inceptor "I need a REST API for a todo app with user authentication"

# Start interactive shell
inceptor shell

Using the Python API

from inceptor import Architect

# Create an architect instance
architect = Architect()

# Generate a solution
solution = architect.generate(
    "E-commerce platform with microservices",
    context={
        "cloud_provider": "aws",
        "container_orchestrator": "kubernetes",
        "monitoring": ["prometheus", "grafana"],
        "budget": "medium"
    },
    levels=4
)

# Export to different formats
print(solution.to_markdown())  # Markdown
print(solution.to_json())      # JSON
print(solution.to_yaml())      # YAML

🏗️ Multi-Level Architecture

Inceptor structures architectures across 5 levels of detail:

Level	Name	Description	Output
1	LIMBO	Problem analysis & decomposition	High-level components
2	DREAM	Component design & interactions	API contracts, Data flows
3	REALITY	Implementation details	Code structure, Tech stack
4	DEEPER	Integration & deployment	CI/CD, Infrastructure
5	DEEPEST	Optimization & scaling	Performance, Monitoring

🛠️ Development

Setup

1. Clone the repository:

   git clone https://github.com/wronai/inceptor.git
   cd inceptor
   

2. Set up the development environment:

   make install
   

Common Tasks

# Run tests
make test

# Run tests with coverage
make test-cov

# Check code style
make lint

# Format code
make format

# Build documentation
make docs

# Run documentation server
make serve-docs

# Build package
make build

# Clean up
make clean

📚 Documentation

For full documentation, please visit https://wronai.github.io/inceptor/

• Installation Guide
• Quick Start
• User Guide
• API Reference
• Examples

🤝 Contributing

Contributions are welcome! Please read our Contributing Guide to get started.

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Ollama for the powerful AI models
• Mistral AI for the 7B model
• The open-source community for invaluable tools and libraries

# 1. Zainstaluj MkDocs
pip install mkdocs-material mkdocstrings[python] mkdocs-awesome-pages-plugin

# 2. Stwórz strukturę docs/
mkdir -p docs/{guide,architecture,api,development,examples,about,assets/{css,js,images}}

# 3. Uruchom development server
mkdocs serve

# 4. Build i deploy
mkdocs build
mkdocs gh-deploy  # GitHub Pages

📚 Struktura dokumentacji:

• Home: Installation, Quick Start, Features
• User Guide: Getting Started, CLI Reference, Examples
• Architecture: Multi-Level Design, Prompts, Ollama Integration
• API Reference: Auto-generated z kodu
• Development: Contributing, Testing, Release Process
• Examples: Real-world use cases, troubleshooting

🎨 Customizacja:

• Theme: Material Design z custom colors
• Logo: Inception-inspired rotating animation
• Terminal: Code examples z animacją
• Social: GitHub, PyPI, Docker links

🔧 Plugin features:

• Search: Zaawansowane z język separatorami
• Git dates: Automatic creation/modification dates
• Minify: Optimized HTML/CSS/JS
• Privacy: GDPR-compliant
• Tags: Content categorization

Teraz wystarczy dodać treść do folderów w docs/ i masz profesjonalną dokumentację gotową na deployment! 🎯

Przykładowa komenda uruchomienia:

mkdocs serve  # http://localhost:8000