https://github.com/wronai/inceptor
"We need to go deeper"
https://github.com/wronai/inceptor
bielik claude cline cursor deepcoding incpetion llm ollama windsurf
Last synced: 2 days ago
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"We need to go deeper"
- Host: GitHub
- URL: https://github.com/wronai/inceptor
- Owner: wronai
- License: apache-2.0
- Created: 2025-06-06T21:22:52.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-06-07T00:01:48.000Z (4 months ago)
- Last Synced: 2025-07-19T15:54:38.114Z (3 months ago)
- Topics: bielik, claude, cline, cursor, deepcoding, incpetion, llm, ollama, windsurf
- Language: HTML
- Homepage: https://wronai.github.io/inceptor/
- Size: 820 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# 🌀 Inceptor
**AI-Powered Multi-Level Solution Architecture Generator**
> **Note**: This project has been refactored for better maintainability and organization. The core functionality remains the same, but the code is now more modular and easier to extend.
[](https://pypi.org/project/inceptor/)
[](https://www.python.org/downloads/)
[](https://github.com/wronai/inceptor/blob/main/LICENSE)
[](https://wronai.github.io/inceptor/)
[](https://github.com/wronai/inceptor/actions/workflows/gh-pages.yml)
[](https://github.com/psf/black)
[](https://pycqa.github.io/isort/)
[](http://mypy-lang.org/)
[](https://flake8.pycqa.org/)
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](https://ollama.ai/) with Mistral:7b model
- 4GB RAM (minimum)
### Installation
```bash
# 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
# Start Ollama server (if not already running)
ollama serve
```
### Basic Usage
```bash
# 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
```python
from inceptor import DreamArchitect, Solution, ArchitectureLevel
# Create an architect instance
architect = DreamArchitect()
# Generate a solution
problem = """
I need a task management system for a small development team.
The team consists of 5 people and uses Python, FastAPI, and PostgreSQL.
The system should have a web interface and REST API.
"""
# Generate solution with 3 levels of detail
solution = architect.inception(problem, max_levels=3)
# Access solution components
print(f"Problem: {solution.problem}")
print(f"Components: {len(solution.architecture.get('limbo', {}).get('components', []))}")
print(f"Tasks: {len(solution.tasks)}")
# Save to JSON
import json
from dataclasses import asdict, is_dataclass
def convert_dataclass(obj):
if is_dataclass(obj):
return {k: convert_dataclass(v) for k, v in asdict(obj).items()}
elif isinstance(obj, (list, tuple)):
return [convert_dataclass(x) for x in obj]
elif isinstance(obj, dict):
return {k: convert_dataclass(v) for k, v in obj.items()}
elif hasattr(obj, 'name'): # For Enums
return obj.name
return obj
with open("solution.json", "w") as f:
json.dump(convert_dataclass(solution), f, indent=2, ensure_ascii=False)
```
## 🏗️ Project Structure
After refactoring, the project has a cleaner, more modular structure:
```
src/inceptor/
├── __init__.py # Package exports and version
├── inceptor.py # Compatibility layer
└── core/ # Core functionality
├── __init__.py # Core package exports
├── enums.py # ArchitectureLevel enum
├── models.py # Solution and Task dataclasses
├── context_extractor.py # Context extraction utilities
├── ollama_client.py # Ollama API client
├── prompt_templates.py # Prompt templates for each level
├── dream_architect.py # Main architecture generation logic
└── utils.py # Utility functions
```
## 🏗️ 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:
```bash
git clone https://github.com/wronai/inceptor.git
cd inceptor
```
2. Set up the development environment:
```bash
# Install Python dependencies
make install
# Install pre-commit hooks
pre-commit install
# Start Ollama server (in a separate terminal)
ollama serve
```
### Common Tasks
```bash
# Install development dependencies
make install
# 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 (http://localhost:8001)
make serve-docs
# Build package
make build
# Clean up
make clean
# Run a local example
python -m src.inceptor.inceptor
```
## 📚 Documentation
For full documentation, please visit [https://wronai.github.io/inceptor/](https://wronai.github.io/inceptor/)
- [Installation Guide](https://wronai.github.io/inceptor/installation/)
- [Quick Start](https://wronai.github.io/inceptor/quick-start/)
- [User Guide](https://wronai.github.io/inceptor/guide/)
- [API Reference](https://wronai.github.io/inceptor/api/)
- [Examples](https://wronai.github.io/inceptor/examples/)
## 🤝 Contributing
Contributions are welcome! Please read our [Contributing Guide](CONTRIBUTING.md) 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](LICENSE) file for details.
## 🙏 Acknowledgments
- [Ollama](https://ollama.ai/) for the powerful AI models
- [Mistral AI](https://mistral.ai/) for the 7B model
- The open-source community for invaluable tools and libraries
```bash
# 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:**
```bash
mkdocs serve # http://localhost:8000
```