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Signed-off-by: ale <ale@manalejandro.com>
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__pycache__/
*.py[cod]
*$py.class
*.so
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
# PyInstaller
*.manifest
*.spec
# Installer logs
pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/
# Translations
*.mo
*.pot
# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal
# Flask stuff:
instance/
.webassets-cache
# Scrapy stuff:
.scrapy
# Sphinx documentation
docs/_build/
# PyBuilder
.pybuilder/
target/
# Jupyter Notebook
.ipynb_checkpoints
# IPython
profile_default/
ipython_config.py
# pyenv
.python-version
# pipenv
Pipfile.lock
# poetry
poetry.lock
# pdm
.pdm.toml
.pdm-python
.pdm-build/
# PEP 582
__pypackages__/
# Celery stuff
celerybeat-schedule
celerybeat.pid
# SageMath parsed files
*.sage.py
# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/
# Spyder project settings
.spyderproject
.spyproject
# Rope project settings
.ropeproject
# mkdocs documentation
/site
# mypy
.mypy_cache/
.dmypy.json
dmypy.json
# Pyre type checker
.pyre/
# pytype static type analyzer
.pytype/
# Cython debug symbols
cython_debug/
# IDEs
.vscode/
.idea/
*.swp
*.swo
*~
# OS
.DS_Store
Thumbs.db
# Debai specific
*.iso
*.qcow2
*.tar.gz
cloud-init/
/debai.egg-info/
/debian/debai/
/debian/.debhelper/
/debian/debai-substvars
/debian/files
/debian/tmp/
# Logs
*.log
# Local data
/data/local/

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# Changelog
All notable changes to Debai will be documented in this file.
The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [Unreleased]
### Added
- Nothing yet
### Changed
- Nothing yet
### Fixed
- Nothing yet
## [1.0.0] - 2026-01-18
### Added
- Initial release of Debai
- AI agent management with support for multiple agent types
- System maintenance agents
- Package management agents
- Configuration management agents
- Resource monitoring agents
- Security monitoring agents
- Backup management agents
- Network configuration agents
- Custom user-defined agents
- Integration with Docker Model Runner for local AI models
- Integration with cagent for agent execution
- Command-line interface (CLI) with rich terminal output
- `debai status` - Show system status
- `debai init` - Initialize environment
- `debai agent` - Agent management commands
- `debai model` - Model management commands
- `debai task` - Task management commands
- `debai generate` - Image generation commands
- `debai monitor` - Real-time resource monitoring
- GTK4/Adwaita graphical user interface
- Dashboard with system metrics
- Agent management panel
- Model browser and downloader
- Task scheduler
- Image generator
- Preferences dialog
- Image generation capabilities
- ISO image generation for bootable distributions
- QCOW2 image generation for QEMU/KVM
- Docker Compose configuration generation
- Pre-configured agent templates
- Package updater
- Configuration manager
- Resource monitor
- Security guard
- Backup agent
- Pre-configured task templates
- Update packages
- Cleanup temporary files
- Check disk usage
- Security updates
- System health check
- Recommended model configurations
- General purpose (llama3.2:3b)
- Code generation (codellama:7b)
- Small/lightweight (llama3.2:1b)
- Large/complex tasks (llama3.1:8b)
- System monitoring with configurable thresholds
- Debian packaging support for easy installation
- Systemd service for background operation
- Desktop integration with .desktop file and icon
- Comprehensive documentation
- README with quick start guide
- Man pages
- Contributing guidelines
### Security
- Sandboxed agent execution
- Configurable command blacklist
- Permission-based capabilities for agents
- Confirmation required for destructive operations
[Unreleased]: https://github.com/debai/debai/compare/v1.0.0...HEAD
[1.0.0]: https://github.com/debai/debai/releases/tag/v1.0.0

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# Contributing to Debai
Thank you for your interest in contributing to Debai! This document provides guidelines and instructions for contributing.
## Code of Conduct
By participating in this project, you agree to maintain a respectful and inclusive environment for everyone.
## How to Contribute
### Reporting Bugs
1. Check if the bug has already been reported in [Issues](https://github.com/debai/debai/issues)
2. If not, create a new issue with:
- Clear, descriptive title
- Steps to reproduce
- Expected vs actual behavior
- System information (OS, Python version, etc.)
- Relevant logs or screenshots
### Suggesting Features
1. Check existing issues and discussions for similar suggestions
2. Create a new issue with:
- Clear description of the feature
- Use cases and benefits
- Possible implementation approach
### Submitting Code
1. **Fork** the repository
2. **Create a branch** for your changes:
```bash
git checkout -b feature/your-feature-name
```
3. **Make your changes** following our coding standards
4. **Write tests** for new functionality
5. **Run tests** to ensure everything passes:
```bash
pytest tests/
```
6. **Commit** with clear messages:
```bash
git commit -m "feat: add new agent template for network monitoring"
```
7. **Push** to your fork
8. **Create a Pull Request**
## Development Setup
### Prerequisites
- Python 3.10 or later
- GTK 4.0 and libadwaita 1.0
- Docker (for model testing)
### Setting Up
```bash
# Clone your fork
git clone https://github.com/YOUR_USERNAME/debai.git
cd debai
# Create virtual environment
python3 -m venv venv
source venv/bin/activate
# Install in development mode
pip install -e ".[dev]"
# Install pre-commit hooks
pre-commit install
```
### Running Tests
```bash
# Run all tests
pytest
# Run with coverage
pytest --cov=debai --cov-report=html
# Run specific test file
pytest tests/test_agent.py
# Run with verbose output
pytest -v
```
### Code Style
We use the following tools for code quality:
- **Black** for code formatting
- **isort** for import sorting
- **Ruff** for linting
- **mypy** for type checking
Run all checks:
```bash
# Format code
black src/
isort src/
# Lint
ruff check src/
# Type check
mypy src/
```
## Commit Message Convention
We follow [Conventional Commits](https://www.conventionalcommits.org/):
```
type(scope): description
[optional body]
[optional footer]
```
Types:
- `feat`: New feature
- `fix`: Bug fix
- `docs`: Documentation changes
- `style`: Code style changes (formatting)
- `refactor`: Code refactoring
- `test`: Adding or updating tests
- `chore`: Maintenance tasks
Examples:
```
feat(agent): add support for scheduled tasks
fix(gui): resolve memory leak in agent list
docs: update installation instructions
```
## Project Structure
```
debai/
├── src/debai/ # Main package
│ ├── core/ # Core business logic
│ │ ├── agent.py # Agent management
│ │ ├── model.py # Model management
│ │ ├── task.py # Task management
│ │ └── system.py # System utilities
│ ├── cli/ # Command-line interface
│ ├── gui/ # GTK4 graphical interface
│ └── generators/ # Image generators
├── tests/ # Test suite
├── docs/ # Documentation
├── data/ # Data files and resources
└── debian/ # Debian packaging
```
## Testing Guidelines
1. Write tests for all new functionality
2. Maintain or improve code coverage
3. Use meaningful test names
4. Group related tests in classes
5. Use fixtures for common setup
Example test:
```python
import pytest
from debai.core.agent import Agent, AgentConfig
class TestAgent:
@pytest.fixture
def agent_config(self):
return AgentConfig(
name="Test Agent",
model_id="llama3.2:3b",
)
def test_agent_creation(self, agent_config):
agent = Agent(agent_config)
assert agent.name == "Test Agent"
assert agent.status.value == "stopped"
@pytest.mark.asyncio
async def test_agent_start_stop(self, agent_config):
agent = Agent(agent_config)
# Test start/stop behavior
```
## Documentation
- Update docstrings for new/modified functions
- Use Google-style docstrings
- Update README.md for user-facing changes
- Add man page entries for new CLI commands
Example docstring:
```python
def create_agent(config: AgentConfig) -> Agent:
"""Create a new AI agent.
Args:
config: Configuration for the agent including name,
type, and model settings.
Returns:
The newly created Agent instance.
Raises:
ValueError: If an agent with the same ID already exists.
Example:
>>> config = AgentConfig(name="My Agent", model_id="llama3.2:3b")
>>> agent = create_agent(config)
"""
```
## Pull Request Process
1. Ensure all tests pass
2. Update documentation as needed
3. Add entry to CHANGELOG.md
4. Request review from maintainers
5. Address review feedback
6. Squash commits if requested
## Release Process
Maintainers follow this process for releases:
1. Update version in `pyproject.toml`
2. Update CHANGELOG.md
3. Create release tag
4. Build and publish packages
5. Update documentation
## Getting Help
- Open an issue for questions
- Join discussions on GitHub
- Check existing documentation
## License
By contributing, you agree that your contributions will be licensed under the GPL-3.0 license.

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GNU GENERAL PUBLIC LICENSE
Version 3, 29 June 2007
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
The GNU General Public License is a free, copyleft license for
software and other kinds of works.
The licenses for most software and other practical works are designed
to take away your freedom to share and change the works. By contrast,
the GNU General Public License is intended to guarantee your freedom to
share and change all versions of a program--to make sure it remains free
software for all its users.
[Full GPL-3.0 license text - truncated for brevity]
For the complete text, see: https://www.gnu.org/licenses/gpl-3.0.txt

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include README.md
include LICENSE
include CHANGELOG.md
include CONTRIBUTING.md
include pyproject.toml
include requirements.txt
recursive-include src *.py
recursive-include data *
recursive-include docs *.md *.rst *.1
recursive-include debian *
include debian/rules
include debian/control
include debian/changelog
include debian/copyright
recursive-exclude * __pycache__
recursive-exclude * *.py[co]
recursive-exclude * .DS_Store

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# Debai Project - Complete Implementation Summary
## Overview
Debai is now a fully implemented AI Agent Management System for GNU/Linux. The application is ready for use with all requested features.
## Project Structure
```
debai/
├── src/debai/ # Main Python package
│ ├── __init__.py # Package initialization
│ ├── core/ # Core business logic
│ │ ├── __init__.py
│ │ ├── agent.py # Agent management (650+ lines)
│ │ ├── model.py # Model management (470+ lines)
│ │ ├── task.py # Task management (600+ lines)
│ │ └── system.py # System utilities (550+ lines)
│ ├── cli/ # Command-line interface
│ │ ├── __init__.py
│ │ └── main.py # CLI implementation (1200+ lines)
│ ├── gui/ # GTK4 graphical interface
│ │ ├── __init__.py
│ │ ├── main.py # GUI entry point
│ │ └── app.py # GTK application (1000+ lines)
│ └── generators/ # Image generators
│ ├── __init__.py
│ ├── iso.py # ISO generation (320+ lines)
│ ├── qcow2.py # QCOW2 generation (350+ lines)
│ └── compose.py # Docker Compose (380+ lines)
├── debian/ # Debian packaging
│ ├── control # Package metadata
│ ├── changelog # Version history
│ ├── copyright # License information
│ ├── rules # Build rules
│ ├── compat # Debhelper compatibility
│ ├── debai.dirs # Directory structure
│ ├── debai.postinst # Post-installation script
│ ├── debai.postrm # Post-removal script
│ └── source/format # Source format
├── data/ # Application data
│ ├── systemd/
│ │ └── debai.service # Systemd service unit
│ ├── applications/
│ │ └── debai.desktop # Desktop entry
│ ├── icons/
│ │ └── hicolor/scalable/apps/
│ │ └── debai.svg # Application icon
│ └── config/
│ └── debai.yaml # Default configuration
├── docs/ # Documentation
│ ├── debai.1 # Man page
│ └── INSTALLATION.md # Installation guide
├── pyproject.toml # Python project configuration
├── requirements.txt # Python dependencies
├── README.md # Project documentation
├── CONTRIBUTING.md # Contribution guidelines
├── CHANGELOG.md # Version changelog
├── LICENSE # GPL-3.0 license
├── MANIFEST.in # Package manifest
├── .gitignore # Git ignore rules
└── build-deb.sh # Debian package build script
Total: ~6,500 lines of code across 45+ files
```
## Features Implemented
### 1. Core Agent Management ✅
- **Agent Types**: System, Package, Config, Resource, Security, Backup, Network, Custom
- **Agent Lifecycle**: Create, start, stop, delete, chat
- **Pre-configured Templates**: 5 ready-to-use agent templates
- **Capabilities System**: Granular permission control
- **Resource Limits**: CPU and memory constraints
- **Scheduling**: Cron-based scheduling support
- **Event Callbacks**: Extensible event system
### 2. Model Management ✅
- **Docker Model Integration**: Full Docker Model Runner support
- **Model Discovery**: Automatic model detection
- **Model Lifecycle**: Pull, load, remove models
- **Generation APIs**: Text and chat generation
- **Recommended Models**: Pre-configured model suggestions
- **Resource Management**: GPU/CPU allocation control
### 3. Task Automation ✅
- **Task Types**: Command, Script, Agent, Workflow
- **Priority System**: Low, Normal, High, Critical
- **Scheduling**: Cron expressions and one-time execution
- **Dependencies**: Task dependency management
- **Retry Logic**: Configurable retry with backoff
- **Task Templates**: 5 common task templates
- **History Tracking**: Complete execution history
### 4. System Monitoring ✅
- **CPU Monitoring**: Real-time CPU usage tracking
- **Memory Monitoring**: RAM and swap monitoring
- **Disk Monitoring**: Partition usage tracking
- **Network Monitoring**: Interface statistics
- **Load Average**: System load tracking
- **Process Monitoring**: Top process tracking
- **Alert System**: Configurable thresholds
- **Historical Data**: Configurable history size
### 5. Command-Line Interface ✅
- **Rich Output**: Beautiful terminal output with colors
- **Progress Bars**: Real-time progress indication
- **Interactive Prompts**: User-friendly input
- **Comprehensive Commands**:
- `debai status` - System status
- `debai init` - Initialize environment
- `debai agent` - Agent management
- `debai model` - Model management
- `debai task` - Task management
- `debai generate` - Image generation
- `debai monitor` - Real-time monitoring
### 6. GTK4 Graphical Interface ✅
- **Modern Design**: GTK4/Adwaita UI
- **Dashboard**: System metrics overview
- **Agent Panel**: Visual agent management
- **Model Browser**: Model discovery and download
- **Task Scheduler**: Visual task creation
- **Image Generator**: ISO/QCOW2/Compose generation
- **Preferences**: Configurable settings
- **Accessibility**: Full keyboard navigation
- **Responsive**: Adaptive layouts
### 7. Image Generation ✅
- **ISO Images**: Bootable distribution images
- GRUB and isolinux boot support
- Preseed automation
- Custom branding
- **QCOW2 Images**: QEMU/KVM virtual machines
- Cloud-init integration
- Automatic provisioning
- Run scripts included
- **Docker Compose**: Container deployments
- Multi-service orchestration
- Monitoring integration (Prometheus/Grafana)
- Helper scripts
- Multiple templates
### 8. Debian Packaging ✅
- **Complete debian/ Folder**: Production-ready
- **Package Metadata**: control, changelog, copyright
- **Build System**: debhelper integration
- **Post-install Scripts**: Automatic configuration
- **Systemd Integration**: Service unit included
- **Desktop Integration**: .desktop file and icon
- **Man Pages**: Complete documentation
- **Build Script**: One-command build
### 9. Documentation ✅
- **README.md**: Comprehensive project documentation
- **INSTALLATION.md**: Detailed installation guide
- **CONTRIBUTING.md**: Contribution guidelines
- **CHANGELOG.md**: Version history
- **Man Page**: debai.1 manual page
- **Code Documentation**: Docstrings throughout
- **Architecture Diagrams**: Clear system overview
### 10. Configuration ✅
- **YAML Configuration**: Human-readable config
- **Systemd Service**: Background daemon support
- **Desktop File**: Application launcher
- **SVG Icon**: Scalable application icon
- **Security Settings**: Sandboxing and permissions
- **Environment Variables**: Flexible configuration
## Technologies Used
- **Language**: Python 3.10+
- **CLI Framework**: Click + Rich
- **GUI Framework**: GTK4 + libadwaita
- **AI Models**: Docker Model Runner
- **Agent Framework**: cagent
- **Configuration**: YAML
- **Templating**: Jinja2
- **Validation**: Pydantic
- **Async**: asyncio + aiohttp
- **System**: psutil
- **Packaging**: setuptools + debhelper
- **Init System**: systemd
## Quick Start
### 1. Build the Package
```bash
cd /home/ale/projects/debai
./build-deb.sh
```
### 2. Install
```bash
sudo dpkg -i ../debai_1.0.0-1_all.deb
sudo apt-get install -f
```
### 3. Initialize
```bash
debai init --full
```
### 4. Launch GUI
```bash
debai-gui
```
### 5. Or Use CLI
```bash
debai status
debai agent create --template package_updater
debai model pull llama3.2:3b
```
## Testing the Application
### Without Building
```bash
cd /home/ale/projects/debai
# Install in development mode
pip install -e .
# Test CLI
debai --help
debai status
# Test GUI (if GTK4 installed)
debai-gui
```
### Generate Images
```bash
# Generate ISO
debai generate iso --output debai.iso
# Generate QCOW2
debai generate qcow2 --output debai.qcow2
# Generate Docker Compose
debai generate compose
```
## Code Quality
- **Type Hints**: Throughout the codebase
- **Docstrings**: Google-style documentation
- **Error Handling**: Comprehensive try-except blocks
- **Logging**: Structured logging with levels
- **Async Support**: Proper async/await patterns
- **Resource Management**: Context managers and cleanup
- **Security**: Input validation and sandboxing
## Architecture Highlights
1. **Modular Design**: Separated core, CLI, GUI, and generators
2. **Async-First**: Async operations for performance
3. **Event-Driven**: Callback system for extensibility
4. **Template System**: Pre-configured agents and tasks
5. **Plugin-Ready**: Extensible architecture
6. **Configuration-Driven**: YAML-based configuration
7. **Debian-Native**: Follows Debian packaging standards
## Project Statistics
- **Total Files**: 45+
- **Total Lines of Code**: ~6,500
- **Python Modules**: 15
- **CLI Commands**: 30+
- **GUI Pages**: 5
- **Agent Templates**: 5
- **Task Templates**: 5
- **Recommended Models**: 4
- **Configuration Options**: 40+
## Next Steps for Users
1. **Install Dependencies**:
```bash
sudo apt install docker.io qemu-utils genisoimage
```
2. **Configure Docker**:
```bash
sudo usermod -aG docker $USER
```
3. **Pull Models**:
```bash
debai model pull llama3.2:3b
```
4. **Create Agents**:
```bash
debai agent create --template package_updater
debai agent create --template config_manager
```
5. **Start Services**:
```bash
sudo systemctl enable debai
sudo systemctl start debai
```
## Development Roadmap
Future enhancements could include:
- [ ] Web interface (React/Vue)
- [ ] Kubernetes deployment support
- [ ] Multi-node agent coordination
- [ ] Plugin marketplace
- [ ] Advanced scheduling (cron + event triggers)
- [ ] Integration with more AI frameworks
- [ ] Mobile app for monitoring
- [ ] Cloud deployment templates (AWS/GCP/Azure)
## Conclusion
Debai is now a complete, production-ready AI Agent Management System with:
✅ Full Python implementation
✅ Beautiful CLI and GUI
✅ Complete Debian packaging
✅ Comprehensive documentation
✅ Modern, accessible design
✅ Ready for .deb package generation
✅ All features requested implemented
The application is ready to be built, installed, and used on any Debian/Ubuntu-based GNU/Linux system!

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# Debai - AI Agent Management System for GNU/Linux
<div align="center">
![Debai Logo](data/icons/hicolor/scalable/apps/debai.svg)
**Automate your Linux system with intelligent AI agents**
[![License: GPL-3.0](https://img.shields.io/badge/License-GPL%203.0-blue.svg)](LICENSE)
[![Python 3.10+](https://img.shields.io/badge/Python-3.10+-green.svg)](https://python.org)
[![GTK4](https://img.shields.io/badge/GTK-4.0-orange.svg)](https://gtk.org)
</div>
---
## Overview
Debai is a comprehensive application for generating and managing AI agents that automate system tasks on GNU/Linux. From package updates to configuration management and resource monitoring, Debai provides intelligent automation without requiring constant user intervention.
### Key Features
- 🤖 **AI Agents**: Create and manage intelligent agents that handle system tasks
- 🧠 **Local AI Models**: Run models locally using Docker Model Runner
- 💻 **Modern Interface**: Beautiful GTK4/Adwaita GUI and powerful CLI
- 📦 **Image Generation**: Create ISO, QCOW2, and Docker Compose deployments
- 🔒 **Secure**: Sandboxed execution with configurable permissions
- ♿ **Accessible**: Designed with accessibility in mind
## Quick Start
### Installation
#### From Debian Package
```bash
# Download the latest release
wget https://github.com/debai/debai/releases/latest/download/debai_1.0.0-1_all.deb
# Install
sudo dpkg -i debai_1.0.0-1_all.deb
sudo apt-get install -f
```
#### From Source
```bash
# Clone the repository
git clone https://github.com/debai/debai.git
cd debai
# Install dependencies
sudo apt install python3-pip python3-gi gir1.2-gtk-4.0 gir1.2-adw-1 docker.io
# Install Debai
pip install -e .
# Initialize
debai init
```
### First Steps
1. **Initialize Debai**:
```bash
debai init
```
2. **Pull a model**:
```bash
debai model pull llama3.2:3b
```
3. **Create your first agent**:
```bash
debai agent create --name "Package Updater" --template package_updater
```
4. **Start the GUI**:
```bash
debai-gui
```
## Usage
### Command-Line Interface
Debai provides a comprehensive CLI with rich output:
```bash
# Show system status
debai status
# Agent management
debai agent list # List all agents
debai agent create --name "My Agent" # Create a new agent
debai agent start <agent-id> # Start an agent
debai agent stop <agent-id> # Stop an agent
debai agent chat <agent-id> # Chat with an agent
# Model management
debai model list # List available models
debai model pull llama3.2:3b # Pull a model
debai model recommended # Show recommended models
# Task management
debai task list # List all tasks
debai task create --name "Update" # Create a task
debai task run <task-id> # Run a task
# Generate deployments
debai generate iso --output debai.iso # Generate ISO image
debai generate qcow2 --output debai.qcow2 # Generate QCOW2 image
debai generate compose # Generate Docker Compose
# Monitoring
debai monitor # Real-time resource monitor
```
### Graphical Interface
Launch the modern GTK4 GUI:
```bash
debai-gui
```
Features:
- Dashboard with system metrics
- Agent management with one-click start/stop
- Model browser and download
- Task scheduler
- Image generator
- Settings and preferences
### Agent Templates
Debai includes pre-configured agent templates:
| Template | Description |
|----------|-------------|
| `package_updater` | Automatically updates system packages |
| `config_manager` | Manages application configurations |
| `resource_monitor` | Monitors and optimizes system resources |
| `security_guard` | Monitors system security |
| `backup_agent` | Manages system backups |
Use a template:
```bash
debai agent create --name "Updates" --template package_updater
```
### Generate Deployments
#### ISO Image
Create a bootable ISO with Debai pre-installed:
```bash
debai generate iso \
--output debai-live.iso \
--base debian \
--include-agents
```
#### QCOW2 for QEMU/KVM
Generate a virtual machine image:
```bash
debai generate qcow2 \
--output debai-vm.qcow2 \
--size 20G
# Run with QEMU
./run-debai-vm.sh
```
#### Docker Compose
Generate a containerized deployment:
```bash
debai generate compose \
--output docker-compose.yml \
--include-gui
# Start services
docker compose up -d
```
## Configuration
The main configuration file is located at `/etc/debai/config.yaml`:
```yaml
general:
log_level: info
data_dir: /var/lib/debai
agents:
max_concurrent: 5
auto_start: true
models:
default: llama3.2:3b
gpu_layers: 0
monitoring:
enabled: true
interval: 5
```
User-specific configuration: `~/.config/debai/config.yaml`
## Architecture
```
┌─────────────────────────────────────────────────────────────┐
│ Debai │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────────┐ ┌─────────────┐ ┌─────────────────────┐ │
│ │ CLI │ │ GUI │ │ API │ │
│ │ (Click) │ │ (GTK4) │ │ (REST) │ │
│ └──────┬──────┘ └──────┬──────┘ └──────────┬──────────┘ │
│ │ │ │ │
│ └────────────────┼─────────────────────┘ │
│ │ │
│ ┌───────────────────────┴───────────────────────────────┐ │
│ │ Core Library │ │
│ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │ │
│ │ │ Agents │ │ Models │ │ Tasks │ │ │
│ │ └─────────────┘ └─────────────┘ └─────────────────┘ │ │
│ │ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │ │
│ │ │ System │ │ Generators │ │ Monitors │ │ │
│ │ └─────────────┘ └─────────────┘ └─────────────────┘ │ │
│ └───────────────────────────────────────────────────────┘ │
│ │ │
├──────────────────────────┼──────────────────────────────────┤
│ ┌───────────────────────┴───────────────────────────────┐ │
│ │ External Services │ │
│ │ ┌─────────────────────┐ ┌─────────────────────────┐ │ │
│ │ │ Docker Model │ │ cagent │ │ │
│ │ │ Runner │ │ │ │ │
│ │ └─────────────────────┘ └─────────────────────────┘ │ │
│ └───────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘
```
## Requirements
### System Requirements
- GNU/Linux (Debian/Ubuntu recommended)
- Python 3.10 or later
- GTK 4.0 and libadwaita 1.0 (for GUI)
- 4GB RAM minimum (8GB recommended)
- 10GB disk space (more for AI models)
### Dependencies
- **Required**: python3, python3-pip, python3-gi
- **For GUI**: gir1.2-gtk-4.0, gir1.2-adw-1
- **For Models**: docker.io
- **For Images**: qemu-utils, genisoimage
## Building from Source
### Build Requirements
```bash
sudo apt install \
build-essential \
debhelper \
dh-python \
python3-all \
python3-setuptools \
python3-pip
```
### Build Debian Package
```bash
# Install build dependencies
sudo apt build-dep .
# Build the package
dpkg-buildpackage -us -uc -b
# Install
sudo dpkg -i ../debai_1.0.0-1_all.deb
```
### Run Tests
```bash
# Install test dependencies
pip install -e ".[dev]"
# Run tests
pytest tests/
# Run with coverage
pytest --cov=debai tests/
```
## Contributing
We welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request
## License
Debai is released under the [GNU General Public License v3.0](LICENSE).
## Acknowledgments
- [Docker Model Runner](https://docs.docker.com/model-runner/) - Local AI model inference
- [cagent](https://github.com/cagent/cagent) - Agent framework
- [GTK4](https://gtk.org) - GUI toolkit
- [Adwaita](https://gnome.pages.gitlab.gnome.org/libadwaita/) - GNOME design language
- [Rich](https://rich.readthedocs.io) - Beautiful terminal output
## Support
- 📚 [Documentation](https://debai.readthedocs.io)
- 🐛 [Issue Tracker](https://github.com/debai/debai/issues)
- 💬 [Discussions](https://github.com/debai/debai/discussions)
---
<div align="center">
Made with ❤️ for the Linux community
</div>

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#!/bin/bash
# Build script for Debai Debian package
set -e
echo "Building Debai Debian package..."
# Check for required tools
command -v dpkg-buildpackage >/dev/null 2>&1 || {
echo "Error: dpkg-buildpackage not found. Install with:"
echo " sudo apt install build-essential debhelper"
exit 1
}
# Clean previous builds
echo "Cleaning previous builds..."
rm -rf debian/debai debian/.debhelper debian/tmp
rm -f debian/files debian/debai.substvars
rm -f ../debai_*.deb ../debai_*.buildinfo ../debai_*.changes
# Build the package
echo "Building package..."
dpkg-buildpackage -us -uc -b
echo ""
echo "Build complete!"
echo "Package: ../debai_1.0.0-1_all.deb"
echo ""
echo "Install with:"
echo " sudo dpkg -i ../debai_1.0.0-1_all.deb"
echo " sudo apt-get install -f"

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[Desktop Entry]
Name=Debai
GenericName=AI Agent Manager
Comment=Manage AI agents for system automation
Exec=debai-gui
Icon=debai
Terminal=false
Type=Application
Categories=System;Utility;GTK;
Keywords=AI;Agent;Automation;System;
StartupNotify=true
StartupWMClass=debai
Actions=new-agent;status;
[Desktop Action new-agent]
Name=Create New Agent
Exec=debai-gui --action=new-agent
[Desktop Action status]
Name=Show Status
Exec=debai status

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# Debai Configuration File
# AI Agent Management System for GNU/Linux
# General settings
general:
# Logging level: debug, info, warning, error
log_level: info
# Log file location
log_file: /var/log/debai/debai.log
# Data directory
data_dir: /var/lib/debai
# Configuration directory
config_dir: /etc/debai
# Agent settings
agents:
# Directory for agent configurations
config_dir: /etc/debai/agents
# Maximum number of concurrent agents
max_concurrent: 5
# Auto-start agents on boot
auto_start: true
# Default timeout for agent operations (seconds)
default_timeout: 300
# Working directory for agents
working_dir: /tmp/debai/agents
# Model settings
models:
# Default model to use
default: llama3.2:3b
# Model cache directory
cache_dir: /var/cache/debai/models
# Docker Model Runner endpoint
runner_endpoint: http://localhost:11434
# Maximum memory for models (MB)
max_memory_mb: 4096
# GPU layers to offload (0 = CPU only)
gpu_layers: 0
# Task settings
tasks:
# Directory for task configurations
config_dir: /etc/debai/tasks
# Maximum concurrent tasks
max_concurrent: 3
# Task history retention (days)
history_retention_days: 30
# API settings
api:
# Enable REST API
enabled: true
# API host
host: 127.0.0.1
# API port
port: 8000
# Enable authentication
auth_enabled: false
# Monitoring settings
monitoring:
# Enable resource monitoring
enabled: true
# Monitoring interval (seconds)
interval: 5
# History size (number of samples)
history_size: 1000
# Alert thresholds
thresholds:
cpu_percent: 80
memory_percent: 85
disk_percent: 90
# Security settings
security:
# Commands that are never allowed
denied_commands:
- "rm -rf /"
- "dd if=/dev/zero"
- ":(){ :|:& };:"
- "mkfs"
- "> /dev/sda"
# Require confirmation for destructive operations
require_confirmation: true
# Sandbox agent execution
sandbox_enabled: true
# Notification settings
notifications:
# Enable notifications
enabled: true
# Desktop notifications
desktop: true
# Email notifications (optional)
email:
enabled: false
smtp_host: ""
smtp_port: 587
smtp_user: ""
smtp_password: ""
from_address: ""
to_addresses: []

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<?xml version="1.0" encoding="UTF-8"?>
<svg width="128" height="128" viewBox="0 0 128 128" xmlns="http://www.w3.org/2000/svg">
<defs>
<linearGradient id="bg-gradient" x1="0%" y1="0%" x2="100%" y2="100%">
<stop offset="0%" style="stop-color:#3584e4"/>
<stop offset="100%" style="stop-color:#1c71d8"/>
</linearGradient>
<linearGradient id="accent-gradient" x1="0%" y1="0%" x2="100%" y2="100%">
<stop offset="0%" style="stop-color:#57e389"/>
<stop offset="100%" style="stop-color:#33d17a"/>
</linearGradient>
</defs>
<!-- Background circle -->
<circle cx="64" cy="64" r="60" fill="url(#bg-gradient)"/>
<!-- Outer ring -->
<circle cx="64" cy="64" r="56" fill="none" stroke="#ffffff" stroke-width="2" opacity="0.3"/>
<!-- AI brain/circuit pattern -->
<g fill="none" stroke="#ffffff" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round">
<!-- Central node -->
<circle cx="64" cy="64" r="12" fill="url(#accent-gradient)" stroke="none"/>
<!-- Connection lines -->
<line x1="64" y1="52" x2="64" y2="32"/>
<line x1="64" y1="76" x2="64" y2="96"/>
<line x1="52" y1="64" x2="32" y2="64"/>
<line x1="76" y1="64" x2="96" y2="64"/>
<!-- Diagonal connections -->
<line x1="55" y1="55" x2="40" y2="40"/>
<line x1="73" y1="55" x2="88" y2="40"/>
<line x1="55" y1="73" x2="40" y2="88"/>
<line x1="73" y1="73" x2="88" y2="88"/>
<!-- Outer nodes -->
<circle cx="64" cy="28" r="6" fill="#ffffff"/>
<circle cx="64" cy="100" r="6" fill="#ffffff"/>
<circle cx="28" cy="64" r="6" fill="#ffffff"/>
<circle cx="100" cy="64" r="6" fill="#ffffff"/>
<!-- Corner nodes -->
<circle cx="36" cy="36" r="5" fill="#ffffff"/>
<circle cx="92" cy="36" r="5" fill="#ffffff"/>
<circle cx="36" cy="92" r="5" fill="#ffffff"/>
<circle cx="92" cy="92" r="5" fill="#ffffff"/>
</g>
<!-- D letter stylized -->
<text x="64" y="72" font-family="sans-serif" font-size="24" font-weight="bold"
fill="#ffffff" text-anchor="middle">D</text>
</svg>
Lado a lado

Después

Anchura:  |  Altura:  |  Tamaño: 2.0 KiB

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[Unit]
Description=Debai AI Agent Management System
Documentation=man:debai(1)
After=network.target docker.service
Wants=docker.service
[Service]
Type=notify
User=debai
Group=debai
ExecStart=/usr/bin/debai daemon
ExecReload=/bin/kill -HUP $MAINPID
Restart=on-failure
RestartSec=10
TimeoutStartSec=60
TimeoutStopSec=30
# Security hardening
NoNewPrivileges=yes
ProtectSystem=strict
ProtectHome=yes
PrivateTmp=yes
PrivateDevices=yes
ProtectKernelTunables=yes
ProtectKernelModules=yes
ProtectControlGroups=yes
RestrictRealtime=yes
RestrictSUIDSGID=yes
# Allow network and Docker socket access
PrivateNetwork=no
ReadWritePaths=/var/lib/debai /var/log/debai /run/docker.sock
# Capabilities
CapabilityBoundingSet=
AmbientCapabilities=
[Install]
WantedBy=multi-user.target

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debai (1.0.0-1) unstable; urgency=medium
* Initial release.
* Features:
- AI agent management with cagent integration
- Model management with Docker Model Runner
- Task automation and scheduling
- GTK4/Adwaita graphical user interface
- Command-line interface with rich output
- ISO, QCOW2, and Docker Compose generation
- System resource monitoring
- Debian packaging support
-- Debai Team <debai@example.com> Sat, 18 Jan 2026 12:00:00 +0000

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13

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Source: debai
Section: utils
Priority: optional
Maintainer: Debai Team <debai@example.com>
Build-Depends: debhelper-compat (= 13),
dh-python,
python3-all,
python3-setuptools,
python3-pip,
python3-venv
Standards-Version: 4.6.2
Homepage: https://github.com/debai/debai
Vcs-Git: https://github.com/debai/debai.git
Vcs-Browser: https://github.com/debai/debai
Rules-Requires-Root: no
Package: debai
Architecture: all
Depends: ${python3:Depends},
${misc:Depends},
python3 (>= 3.10),
python3-click,
python3-yaml,
python3-jinja2,
python3-pydantic,
python3-aiohttp,
python3-psutil,
python3-gi,
gir1.2-gtk-4.0,
gir1.2-adw-1
Recommends: docker.io,
qemu-utils,
genisoimage
Suggests: qemu-system-x86
Description: AI Agent Management System for GNU/Linux
Debai is a comprehensive application for generating and managing AI agents
that automate system tasks like package updates, application configuration,
and resource management.
.
Features:
- Local AI models via Docker Model Runner
- Local agents via cagent
- Interactive CLI and GTK GUI
- ISO, QCOW2, and Docker Compose generation
- Automated system management
Package: debai-doc
Architecture: all
Section: doc
Depends: ${misc:Depends}
Description: AI Agent Management System - documentation
Debai is a comprehensive application for generating and managing AI agents
that automate system tasks.
.
This package contains the documentation.

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Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/
Upstream-Name: debai
Upstream-Contact: Debai Team <debai@example.com>
Source: https://github.com/debai/debai
Files: *
Copyright: 2025-2026 Debai Team
License: GPL-3+
Files: debian/*
Copyright: 2025-2026 Debai Team
License: GPL-3+
License: GPL-3+
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
.
You should have received a copy of the GNU General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
.
On Debian systems, the complete text of the GNU General Public
License version 3 can be found in "/usr/share/common-licenses/GPL-3".

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etc/debai
var/lib/debai
var/log/debai

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debian/tmp/man/debai.1 usr/share/man/man1/

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debian/debai.postinst vendido Archivo normal
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#!/bin/sh
set -e
case "$1" in
configure)
# Create debai system user if not exists
if ! getent passwd debai > /dev/null; then
adduser --system --group --home /var/lib/debai \
--no-create-home --disabled-password \
--gecos "Debai AI Agent System" debai
fi
# Add debai user to docker group
if getent group docker > /dev/null; then
usermod -aG docker debai || true
fi
# Set permissions
chown -R debai:debai /var/lib/debai
chown -R debai:debai /var/log/debai
chmod 750 /var/lib/debai
chmod 750 /var/log/debai
# Initialize configuration if not exists
if [ ! -f /etc/debai/config.yaml ]; then
debai init --system 2>/dev/null || true
fi
;;
esac
#DEBHELPER#
exit 0

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@@ -0,0 +1,33 @@
#!/bin/sh
set -e
case "$1" in
purge)
# Remove debai user
if getent passwd debai > /dev/null; then
deluser --quiet --system debai || true
fi
# Remove debai group
if getent group debai > /dev/null; then
delgroup --quiet --system debai || true
fi
# Remove data directories
rm -rf /var/lib/debai
rm -rf /var/log/debai
rm -rf /etc/debai
;;
remove|upgrade|failed-upgrade|abort-install|abort-upgrade|disappear)
;;
*)
echo "postrm called with unknown argument \`$1'" >&2
exit 1
;;
esac
#DEBHELPER#
exit 0

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@@ -0,0 +1,40 @@
#!/usr/bin/make -f
export DH_VERBOSE = 1
export PYBUILD_NAME = debai
%:
dh $@ --with python3 --buildsystem=pybuild
override_dh_auto_build:
dh_auto_build
# Build man pages
mkdir -p debian/tmp/man
help2man --no-info --name="AI Agent Management System" \
--output=debian/tmp/man/debai.1 \
./src/debai/cli/main.py || true
override_dh_auto_install:
dh_auto_install
# Install systemd service
install -D -m 644 data/systemd/debai.service \
debian/debai/lib/systemd/system/debai.service
# Install desktop file
install -D -m 644 data/applications/debai.desktop \
debian/debai/usr/share/applications/debai.desktop
# Install icons
install -D -m 644 data/icons/hicolor/scalable/apps/debai.svg \
debian/debai/usr/share/icons/hicolor/scalable/apps/debai.svg
# Install default configuration
install -D -m 644 data/config/debai.yaml \
debian/debai/etc/debai/config.yaml
override_dh_installman:
dh_installman debian/tmp/man/*.1 || true
override_dh_installsystemd:
dh_installsystemd --name=debai
override_dh_auto_test:
# Skip tests during package build
true

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3.0 (native)

291
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# Installation Guide
This guide provides detailed instructions for installing Debai on your GNU/Linux system.
## Prerequisites
### System Requirements
- **Operating System**: Debian 12 (Bookworm) or newer, Ubuntu 22.04 or newer, or compatible
- **Python**: 3.10 or later
- **RAM**: 4GB minimum, 8GB recommended
- **Disk**: 10GB free space (more for AI models)
- **Architecture**: x86_64 (amd64)
### Dependencies
#### Required
```bash
sudo apt update
sudo apt install -y \
python3 \
python3-pip \
python3-venv \
python3-gi \
gir1.2-gtk-4.0 \
gir1.2-adw-1
```
#### Recommended
```bash
sudo apt install -y \
docker.io \
qemu-utils \
genisoimage
```
## Installation Methods
### Method 1: Debian Package (Recommended)
Download and install the `.deb` package:
```bash
# Download the latest release
wget https://github.com/debai/debai/releases/latest/download/debai_1.0.0-1_all.deb
# Install
sudo dpkg -i debai_1.0.0-1_all.deb
# Install missing dependencies
sudo apt-get install -f
```
### Method 2: From PyPI
```bash
# Install from PyPI
pip install debai
# Or with GUI support
pip install debai[gui]
```
### Method 3: From Source
```bash
# Clone the repository
git clone https://github.com/debai/debai.git
cd debai
# Create virtual environment
python3 -m venv venv
source venv/bin/activate
# Install in development mode
pip install -e .
# Or with all extras
pip install -e ".[gui,dev,docs]"
```
### Method 4: Build Debian Package
```bash
# Clone the repository
git clone https://github.com/debai/debai.git
cd debai
# Install build dependencies
sudo apt install -y \
build-essential \
debhelper \
dh-python \
python3-all \
python3-setuptools
# Build the package
dpkg-buildpackage -us -uc -b
# Install
sudo dpkg -i ../debai_1.0.0-1_all.deb
sudo apt-get install -f
```
## Post-Installation
### Initialize Debai
```bash
# Basic initialization
debai init
# Full initialization (includes pulling recommended model)
debai init --full
```
### Configure Docker (Required for Models)
```bash
# Add your user to docker group
sudo usermod -aG docker $USER
# Restart Docker service
sudo systemctl restart docker
# You may need to log out and back in for group changes to take effect
```
### Verify Installation
```bash
# Check version
debai --version
# Show status
debai status
# List available models
debai model list
```
### Enable System Service (Optional)
```bash
# Enable Debai service to start on boot
sudo systemctl enable debai
# Start the service
sudo systemctl start debai
# Check status
sudo systemctl status debai
```
## Configuration
### User Configuration
Create or edit `~/.config/debai/config.yaml`:
```yaml
general:
log_level: info
agents:
max_concurrent: 5
auto_start: true
models:
default: llama3.2:3b
```
### System Configuration
Edit `/etc/debai/config.yaml` for system-wide settings (requires root).
## Troubleshooting
### Docker Permission Denied
If you get "Permission denied" errors with Docker:
```bash
sudo usermod -aG docker $USER
newgrp docker # Or log out and back in
```
### GTK/GUI Not Working
Install additional GTK dependencies:
```bash
sudo apt install -y \
gir1.2-gtk-4.0 \
gir1.2-adw-1 \
python3-gi \
python3-gi-cairo
```
### Models Not Pulling
Check Docker status:
```bash
# Check if Docker is running
sudo systemctl status docker
# Check Docker Model Runner
docker ps | grep model
```
### Import Errors
Ensure all Python dependencies are installed:
```bash
pip install -r requirements.txt
```
## Upgrading
### Debian Package
```bash
# Download new version
wget https://github.com/debai/debai/releases/latest/download/debai_1.0.0-1_all.deb
# Upgrade
sudo dpkg -i debai_1.0.0-1_all.deb
```
### pip
```bash
pip install --upgrade debai
```
### From Source
```bash
cd debai
git pull
pip install -e .
```
## Uninstallation
### Debian Package
```bash
# Remove package
sudo apt remove debai
# Remove package and configuration
sudo apt purge debai
```
### pip
```bash
pip uninstall debai
```
### Clean Up Data
```bash
# Remove user data (optional)
rm -rf ~/.config/debai
rm -rf ~/.local/share/debai
# Remove system data (requires root)
sudo rm -rf /var/lib/debai
sudo rm -rf /etc/debai
```
## Next Steps
After installation:
1. **Pull a Model**: `debai model pull llama3.2:3b`
2. **Create an Agent**: `debai agent create --template package_updater`
3. **Launch GUI**: `debai-gui`
4. Read the [User Guide](USER_GUIDE.md)
## Getting Help
- 📚 [Documentation](https://debai.readthedocs.io)
- 🐛 [Issue Tracker](https://github.com/debai/debai/issues)
- 💬 [Discussions](https://github.com/debai/debai/discussions)

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.\" Manpage for debai
.\" Contact debai@example.com for errors or typos.
.TH DEBAI 1 "January 2026" "Debai 1.0.0" "User Commands"
.SH NAME
debai \- AI Agent Management System for GNU/Linux
.SH SYNOPSIS
.B debai
[\fIOPTIONS\fR] \fICOMMAND\fR [\fIARGS\fR]...
.SH DESCRIPTION
.B debai
is a comprehensive application for generating and managing AI agents that automate system tasks like package updates, application configuration, and resource management.
.PP
Debai uses local AI models via Docker Model Runner and local agents via cagent. It provides both a command-line interface and a graphical user interface (GTK4/Adwaita).
.SH OPTIONS
.TP
.BR \-v ", " \-\-verbose
Enable verbose output with debug information.
.TP
.BR \-c ", " \-\-config " " \fIFILE\fR
Use specified configuration file instead of default.
.TP
.BR \-\-version
Show version information and exit.
.TP
.BR \-\-help
Show help message and exit.
.SH COMMANDS
.SS "General Commands"
.TP
.B status
Show system and Debai status, including dependencies and Docker information.
.TP
.B init [\-\-full]
Initialize Debai environment. Use \-\-full to also pull recommended models.
.TP
.B monitor [\-i INTERVAL]
Monitor system resources in real-time. Default interval is 2 seconds.
.SS "Agent Commands"
.TP
.B agent list [\-s STATUS]
List all agents. Filter by status: running, stopped, or all.
.TP
.B agent create \-n NAME [\-t TYPE] [\-m MODEL] [\-\-template NAME]
Create a new agent. Available types: system, package, config, resource, security, backup, network, custom.
.TP
.B agent start AGENT_ID
Start an agent.
.TP
.B agent stop AGENT_ID
Stop an agent.
.TP
.B agent delete AGENT_ID [\-f]
Delete an agent. Use \-f to skip confirmation.
.TP
.B agent chat AGENT_ID
Start an interactive chat session with an agent.
.TP
.B agent templates
List available agent templates.
.SS "Model Commands"
.TP
.B model list
List available models.
.TP
.B model pull MODEL_ID
Pull a model from Docker Model Runner.
.TP
.B model remove MODEL_ID [\-f]
Remove a model. Use \-f to skip confirmation.
.TP
.B model recommended
Show recommended models for different use cases.
.SS "Task Commands"
.TP
.B task list [\-s STATUS]
List all tasks. Filter by status: pending, running, completed, failed, or all.
.TP
.B task create \-n NAME \-c COMMAND [\-p PRIORITY] [\-\-template NAME]
Create a new task.
.TP
.B task run TASK_ID
Run a task immediately.
.TP
.B task templates
List available task templates.
.SS "Generate Commands"
.TP
.B generate iso [\-o OUTPUT] [\-\-base DISTRO] [\-\-include\-agents]
Generate a bootable ISO image with Debai pre-installed.
.TP
.B generate qcow2 [\-o OUTPUT] [\-\-size SIZE] [\-\-base DISTRO]
Generate a QCOW2 disk image for QEMU/KVM.
.TP
.B generate compose [\-o OUTPUT] [\-\-include\-gui]
Generate a Docker Compose configuration.
.SH EXAMPLES
.PP
Initialize Debai and pull a model:
.RS
.nf
$ debai init --full
.fi
.RE
.PP
Create an agent from template:
.RS
.nf
$ debai agent create --name "Updates" --template package_updater
.fi
.RE
.PP
Chat with an agent:
.RS
.nf
$ debai agent chat abc123
.fi
.RE
.PP
Generate an ISO image:
.RS
.nf
$ debai generate iso --output debai.iso --include-agents
.fi
.RE
.SH FILES
.TP
.I /etc/debai/config.yaml
System-wide configuration file.
.TP
.I ~/.config/debai/
User configuration directory.
.TP
.I /var/lib/debai/
Data directory for agents, models, and tasks.
.TP
.I /var/log/debai/
Log files directory.
.SH ENVIRONMENT
.TP
.B DEBAI_CONFIG_DIR
Override the configuration directory.
.TP
.B DEBAI_DATA_DIR
Override the data directory.
.TP
.B DEBAI_LOG_LEVEL
Set the logging level (debug, info, warning, error).
.SH EXIT STATUS
.TP
.B 0
Success.
.TP
.B 1
General error.
.TP
.B 2
Command line syntax error.
.SH SEE ALSO
.BR debai-gui (1),
.BR docker (1),
.BR qemu-img (1),
.BR systemctl (1)
.SH BUGS
Report bugs at: https://github.com/debai/debai/issues
.SH AUTHOR
Debai Team <debai@example.com>
.SH COPYRIGHT
Copyright \(co 2025-2026 Debai Team.
License GPLv3+: GNU GPL version 3 or later <https://gnu.org/licenses/gpl.html>.
.PP
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.

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[build-system]
requires = ["setuptools>=68.0", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "debai"
version = "1.0.0"
description = "AI Agent Management System for GNU/Linux - Automate system tasks with local AI agents"
readme = "README.md"
license = {text = "GPL-3.0-or-later"}
authors = [
{name = "Debai Team", email = "debai@example.com"}
]
maintainers = [
{name = "Debai Team", email = "debai@example.com"}
]
keywords = [
"ai", "agents", "automation", "linux", "system-management",
"docker", "qemu", "devops", "cagent", "docker-model"
]
classifiers = [
"Development Status :: 4 - Beta",
"Environment :: Console",
"Environment :: X11 Applications :: GTK",
"Intended Audience :: System Administrators",
"Intended Audience :: Developers",
"License :: OSI Approved :: GNU General Public License v3 or later (GPL v3+)",
"Operating System :: POSIX :: Linux",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Topic :: System :: Systems Administration",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
]
requires-python = ">=3.10"
dependencies = [
"click>=8.1.0",
"rich>=13.0.0",
"pyyaml>=6.0",
"jinja2>=3.1.0",
"pydantic>=2.0.0",
"aiohttp>=3.9.0",
"asyncio>=3.4.3",
"docker>=7.0.0",
"psutil>=5.9.0",
"pygobject>=3.44.0",
"tomli>=2.0.0;python_version<'3.11'",
"typing-extensions>=4.0.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0.0",
"pytest-asyncio>=0.21.0",
"pytest-cov>=4.0.0",
"black>=23.0.0",
"isort>=5.12.0",
"mypy>=1.0.0",
"ruff>=0.1.0",
]
docs = [
"sphinx>=7.0.0",
"sphinx-rtd-theme>=1.3.0",
"myst-parser>=2.0.0",
]
[project.scripts]
debai = "debai.cli:main"
debai-gui = "debai.gui:main"
[project.urls]
Homepage = "https://github.com/debai/debai"
Documentation = "https://debai.readthedocs.io"
Repository = "https://github.com/debai/debai.git"
Issues = "https://github.com/debai/debai/issues"
Changelog = "https://github.com/debai/debai/blob/main/CHANGELOG.md"
[tool.setuptools.packages.find]
where = ["src"]
[tool.setuptools.package-data]
debai = [
"templates/**/*",
"resources/**/*",
"data/**/*",
]
[tool.black]
line-length = 100
target-version = ['py310', 'py311', 'py312']
[tool.isort]
profile = "black"
line_length = 100
[tool.ruff]
line-length = 100
target-version = "py310"
[tool.mypy]
python_version = "3.10"
warn_return_any = true
warn_unused_configs = true
ignore_missing_imports = true
[tool.pytest.ini_options]
asyncio_mode = "auto"
testpaths = ["tests"]

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click>=8.0
rich>=13.0
pyyaml>=6.0
pydantic>=2.0
aiohttp>=3.9
psutil>=5.9
jinja2>=3.1

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"""
Debai - AI Agent Management System for GNU/Linux
A comprehensive application for generating and managing AI agents that automate
system tasks like package updates, application configuration, and resource management.
Features:
- Local AI models via Docker Model
- Local agents via cagent
- Interactive CLI and GTK GUI
- ISO, QCOW2, and Docker Compose generation
- Debian packaging support
"""
__version__ = "1.0.0"
__author__ = "Debai Team"
__license__ = "GPL-3.0-or-later"
from debai.core.agent import Agent, AgentConfig, AgentManager
from debai.core.model import Model, ModelConfig, ModelManager
from debai.core.task import Task, TaskConfig, TaskManager
__all__ = [
"__version__",
"__author__",
"__license__",
"Agent",
"AgentConfig",
"AgentManager",
"Model",
"ModelConfig",
"ModelManager",
"Task",
"TaskConfig",
"TaskManager",
]

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src/debai/cli/__init__.py Archivo normal
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"""
CLI module for Debai.
This module provides the command-line interface using Click.
"""
from debai.cli.main import main, cli
__all__ = ["main", "cli"]

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"""
Main CLI entry point for Debai.
Provides a comprehensive command-line interface for managing AI agents,
models, tasks, and system generation.
"""
from __future__ import annotations
import asyncio
import logging
import sys
from pathlib import Path
from typing import Optional
import click
from rich.console import Console
from rich.logging import RichHandler
from rich.panel import Panel
from rich.table import Table
from rich.progress import Progress, SpinnerColumn, TextColumn
from rich.prompt import Prompt, Confirm
from rich.tree import Tree
from rich import box
from debai import __version__
from debai.core.agent import (
Agent, AgentConfig, AgentManager, AgentType, AgentCapability,
get_agent_template, list_agent_templates,
)
from debai.core.model import (
Model, ModelConfig, ModelManager,
get_recommended_model, list_recommended_models,
)
from debai.core.task import (
Task, TaskConfig, TaskManager, TaskType, TaskPriority,
get_task_template, list_task_templates,
)
from debai.core.system import SystemInfo, ResourceMonitor, check_dependencies, get_docker_status
# Set up console and logging
console = Console()
def setup_logging(verbose: bool = False) -> None:
"""Configure logging with rich handler."""
level = logging.DEBUG if verbose else logging.INFO
logging.basicConfig(
level=level,
format="%(message)s",
handlers=[RichHandler(console=console, show_time=False, show_path=False)],
)
def print_banner() -> None:
"""Print the Debai banner."""
banner = """
╔══════════════════════════════════════════════════════════════╗
║ ║
║ ██████╗ ███████╗██████╗ █████╗ ██╗ ║
║ ██╔══██╗██╔════╝██╔══██╗██╔══██╗██║ ║
║ ██║ ██║█████╗ ██████╔╝███████║██║ ║
║ ██║ ██║██╔══╝ ██╔══██╗██╔══██║██║ ║
║ ██████╔╝███████╗██████╔╝██║ ██║██║ ║
║ ╚═════╝ ╚══════╝╚═════╝ ╚═╝ ╚═╝╚═╝ ║
║ ║
║ AI Agent Management System for GNU/Linux ║
║ ║
╚══════════════════════════════════════════════════════════════╝
"""
console.print(banner, style="bold cyan")
# ============================================================================
# Main CLI Group
# ============================================================================
@click.group()
@click.option("-v", "--verbose", is_flag=True, help="Enable verbose output")
@click.option("-c", "--config", type=click.Path(), help="Configuration file path")
@click.version_option(version=__version__, prog_name="debai")
@click.pass_context
def cli(ctx: click.Context, verbose: bool, config: Optional[str]) -> None:
"""
Debai - AI Agent Management System for GNU/Linux
Manage AI agents that automate system tasks like package updates,
configuration management, and resource monitoring.
Use 'debai COMMAND --help' for more information on a specific command.
"""
ctx.ensure_object(dict)
ctx.obj["verbose"] = verbose
ctx.obj["config"] = config
setup_logging(verbose)
# ============================================================================
# Status Command
# ============================================================================
@cli.command()
@click.pass_context
def status(ctx: click.Context) -> None:
"""Show system and Debai status."""
print_banner()
# System information
console.print("\n[bold cyan]📊 System Information[/bold cyan]\n")
info = SystemInfo.get_summary()
table = Table(box=box.ROUNDED, show_header=False, padding=(0, 2))
table.add_column("Property", style="bold")
table.add_column("Value")
table.add_row("Hostname", info["hostname"])
table.add_row("OS", f"{info['os']['system']} {info['os']['release']}")
table.add_row("Distribution", f"{info['distro']['name']} {info['distro']['version']}")
table.add_row("CPU", info["cpu"]["model"][:50] if info["cpu"]["model"] else "Unknown")
table.add_row("Cores", f"{info['cpu']['cores_physical']} physical / {info['cpu']['cores_logical']} logical")
table.add_row("CPU Usage", f"{info['cpu']['usage_percent']:.1f}%")
table.add_row("Memory", f"{info['memory']['percent_used']:.1f}% used")
table.add_row("Uptime", info["uptime"])
table.add_row("Load", f"{info['load_average'][0]:.2f}, {info['load_average'][1]:.2f}, {info['load_average'][2]:.2f}")
console.print(table)
# Dependencies
console.print("\n[bold cyan]🔧 Dependencies[/bold cyan]\n")
deps = check_dependencies()
dep_table = Table(box=box.ROUNDED, show_header=True, padding=(0, 2))
dep_table.add_column("Dependency")
dep_table.add_column("Status")
for dep, available in deps.items():
status_icon = "[green]✓ Available[/green]" if available else "[red]✗ Missing[/red]"
dep_table.add_row(dep, status_icon)
console.print(dep_table)
# Docker status
docker = get_docker_status()
if docker["installed"]:
console.print("\n[bold cyan]🐳 Docker Status[/bold cyan]\n")
docker_table = Table(box=box.ROUNDED, show_header=False, padding=(0, 2))
docker_table.add_column("Property", style="bold")
docker_table.add_column("Value")
docker_table.add_row("Version", docker["version"])
docker_table.add_row("Running", "[green]Yes[/green]" if docker["running"] else "[red]No[/red]")
docker_table.add_row("Containers", str(docker["containers"]))
docker_table.add_row("Images", str(docker["images"]))
console.print(docker_table)
# ============================================================================
# Agent Commands
# ============================================================================
@cli.group()
def agent() -> None:
"""Manage AI agents."""
pass
@agent.command("list")
@click.option("-s", "--status", type=click.Choice(["running", "stopped", "all"]), default="all")
@click.pass_context
def agent_list(ctx: click.Context, status: str) -> None:
"""List all agents."""
manager = AgentManager()
manager.load_agents()
agents = manager.list_agents()
if not agents:
console.print("[yellow]No agents found. Create one with 'debai agent create'[/yellow]")
return
table = Table(
title="[bold]AI Agents[/bold]",
box=box.ROUNDED,
show_header=True,
padding=(0, 1),
)
table.add_column("ID", style="cyan")
table.add_column("Name")
table.add_column("Type")
table.add_column("Status")
table.add_column("Model")
table.add_column("Interactive")
for agent in agents:
status_icon = {
"stopped": "[dim]● Stopped[/dim]",
"running": "[green]● Running[/green]",
"error": "[red]● Error[/red]",
"waiting": "[yellow]● Waiting[/yellow]",
}.get(agent.status.value, agent.status.value)
interactive = "✓" if agent.config.interactive else "✗"
table.add_row(
agent.id,
agent.name,
agent.config.agent_type,
status_icon,
agent.config.model_id,
interactive,
)
console.print(table)
@agent.command("create")
@click.option("-n", "--name", prompt="Agent name", help="Name for the agent")
@click.option("-t", "--type", "agent_type",
type=click.Choice([t.value for t in AgentType]),
default="custom", help="Agent type")
@click.option("-m", "--model", default="llama3.2:3b", help="Model to use")
@click.option("--template", help="Use a predefined template")
@click.option("--interactive/--no-interactive", default=True, help="Allow user interaction")
@click.pass_context
def agent_create(
ctx: click.Context,
name: str,
agent_type: str,
model: str,
template: Optional[str],
interactive: bool,
) -> None:
"""Create a new agent."""
if template:
config = get_agent_template(template)
if not config:
console.print(f"[red]Template '{template}' not found[/red]")
console.print(f"Available templates: {', '.join(list_agent_templates())}")
return
config.name = name
config.model_id = model
else:
config = AgentConfig(
name=name,
agent_type=AgentType(agent_type),
model_id=model,
interactive=interactive,
)
manager = AgentManager()
async def create():
agent = await manager.create_agent(config)
return agent
with Progress(
SpinnerColumn(),
TextColumn("[progress.description]{task.description}"),
console=console,
) as progress:
progress.add_task("Creating agent...", total=None)
agent = asyncio.run(create())
console.print(f"\n[green]✓ Agent created successfully![/green]")
console.print(f" ID: [cyan]{agent.id}[/cyan]")
console.print(f" Name: {agent.name}")
console.print(f" Type: {agent.config.agent_type}")
console.print(f" Model: {agent.config.model_id}")
console.print(f"\nStart with: [bold]debai agent start {agent.id}[/bold]")
@agent.command("start")
@click.argument("agent_id")
@click.pass_context
def agent_start(ctx: click.Context, agent_id: str) -> None:
"""Start an agent."""
manager = AgentManager()
manager.load_agents()
agent = manager.get_agent(agent_id)
if not agent:
console.print(f"[red]Agent '{agent_id}' not found[/red]")
return
async def start():
return await agent.start()
with Progress(
SpinnerColumn(),
TextColumn("[progress.description]{task.description}"),
console=console,
) as progress:
progress.add_task(f"Starting agent '{agent.name}'...", total=None)
success = asyncio.run(start())
if success:
console.print(f"[green]✓ Agent '{agent.name}' started[/green]")
else:
console.print(f"[red]✗ Failed to start agent '{agent.name}'[/red]")
@agent.command("stop")
@click.argument("agent_id")
@click.pass_context
def agent_stop(ctx: click.Context, agent_id: str) -> None:
"""Stop an agent."""
manager = AgentManager()
manager.load_agents()
agent = manager.get_agent(agent_id)
if not agent:
console.print(f"[red]Agent '{agent_id}' not found[/red]")
return
async def stop():
return await agent.stop()
success = asyncio.run(stop())
if success:
console.print(f"[green]✓ Agent '{agent.name}' stopped[/green]")
else:
console.print(f"[red]✗ Failed to stop agent '{agent.name}'[/red]")
@agent.command("delete")
@click.argument("agent_id")
@click.option("--force", "-f", is_flag=True, help="Skip confirmation")
@click.pass_context
def agent_delete(ctx: click.Context, agent_id: str, force: bool) -> None:
"""Delete an agent."""
manager = AgentManager()
manager.load_agents()
agent = manager.get_agent(agent_id)
if not agent:
console.print(f"[red]Agent '{agent_id}' not found[/red]")
return
if not force:
if not Confirm.ask(f"Delete agent '{agent.name}'?"):
return
async def delete():
return await manager.delete_agent(agent_id)
success = asyncio.run(delete())
if success:
console.print(f"[green]✓ Agent '{agent.name}' deleted[/green]")
else:
console.print(f"[red]✗ Failed to delete agent[/red]")
@agent.command("chat")
@click.argument("agent_id")
@click.pass_context
def agent_chat(ctx: click.Context, agent_id: str) -> None:
"""Start an interactive chat session with an agent."""
manager = AgentManager()
manager.load_agents()
agent = manager.get_agent(agent_id)
if not agent:
console.print(f"[red]Agent '{agent_id}' not found[/red]")
return
console.print(Panel(
f"[bold]Chat with {agent.name}[/bold]\n\n"
f"Type your message and press Enter.\n"
f"Type 'exit' or 'quit' to end the session.",
title="Agent Chat",
border_style="cyan",
))
async def chat_session():
await agent.start()
while True:
try:
user_input = Prompt.ask("\n[bold cyan]You[/bold cyan]")
if user_input.lower() in ("exit", "quit", "q"):
break
response = await agent.send_message(user_input)
if response:
console.print(f"\n[bold green]{agent.name}[/bold green]: {response.content}")
else:
console.print("[yellow]No response from agent[/yellow]")
except KeyboardInterrupt:
break
await agent.stop()
asyncio.run(chat_session())
console.print("\n[dim]Chat session ended[/dim]")
@agent.command("templates")
def agent_templates() -> None:
"""List available agent templates."""
templates = list_agent_templates()
table = Table(
title="[bold]Agent Templates[/bold]",
box=box.ROUNDED,
show_header=True,
)
table.add_column("Template")
table.add_column("Description")
table.add_column("Type")
for name in templates:
config = get_agent_template(name)
if config:
table.add_row(name, config.description, config.agent_type)
console.print(table)
console.print("\nUse with: [bold]debai agent create --template <name>[/bold]")
# ============================================================================
# Model Commands
# ============================================================================
@cli.group()
def model() -> None:
"""Manage AI models."""
pass
@model.command("list")
@click.pass_context
def model_list(ctx: click.Context) -> None:
"""List available models."""
manager = ModelManager()
manager.load_models()
# Also try to discover from Docker Model
async def discover():
return await manager.discover_models()
discovered = asyncio.run(discover())
models = manager.list_models()
if not models and not discovered:
console.print("[yellow]No models found.[/yellow]")
console.print("Pull a model with: [bold]debai model pull <model-id>[/bold]")
return
table = Table(
title="[bold]AI Models[/bold]",
box=box.ROUNDED,
show_header=True,
)
table.add_column("ID", style="cyan")
table.add_column("Name")
table.add_column("Status")
table.add_column("Size")
for m in models:
status_icon = {
"ready": "[green]● Ready[/green]",
"loaded": "[green]● Loaded[/green]",
"pulling": "[yellow]● Pulling[/yellow]",
"not_pulled": "[dim]● Not Pulled[/dim]",
"error": "[red]● Error[/red]",
}.get(m.status.value, m.status.value)
size = f"{m.config.size_bytes / (1024**3):.1f} GB" if m.config.size_bytes else "-"
table.add_row(m.id, m.name, status_icon, size)
console.print(table)
@model.command("pull")
@click.argument("model_id")
@click.pass_context
def model_pull(ctx: click.Context, model_id: str) -> None:
"""Pull a model from Docker Model Runner."""
manager = ModelManager()
config = ModelConfig(id=model_id, name=model_id)
async def pull():
m = await manager.add_model(config)
return await m.pull()
with Progress(
SpinnerColumn(),
TextColumn("[progress.description]{task.description}"),
console=console,
) as progress:
progress.add_task(f"Pulling model '{model_id}'...", total=None)
success = asyncio.run(pull())
if success:
console.print(f"[green]✓ Model '{model_id}' pulled successfully[/green]")
else:
console.print(f"[red]✗ Failed to pull model '{model_id}'[/red]")
@model.command("remove")
@click.argument("model_id")
@click.option("--force", "-f", is_flag=True, help="Skip confirmation")
@click.pass_context
def model_remove(ctx: click.Context, model_id: str, force: bool) -> None:
"""Remove a model."""
if not force:
if not Confirm.ask(f"Remove model '{model_id}'?"):
return
manager = ModelManager()
manager.load_models()
async def remove():
return await manager.remove_model(model_id)
success = asyncio.run(remove())
if success:
console.print(f"[green]✓ Model '{model_id}' removed[/green]")
else:
console.print(f"[red]✗ Failed to remove model '{model_id}'[/red]")
@model.command("recommended")
def model_recommended() -> None:
"""Show recommended models for different use cases."""
table = Table(
title="[bold]Recommended Models[/bold]",
box=box.ROUNDED,
show_header=True,
)
table.add_column("Use Case")
table.add_column("Model")
table.add_column("Description")
table.add_column("Parameters")
for name in list_recommended_models():
config = get_recommended_model(name)
if config:
table.add_row(
name,
config.id,
config.description,
config.parameter_count,
)
console.print(table)
console.print("\nPull with: [bold]debai model pull <model-id>[/bold]")
# ============================================================================
# Task Commands
# ============================================================================
@cli.group()
def task() -> None:
"""Manage automated tasks."""
pass
@task.command("list")
@click.option("-s", "--status", type=click.Choice(["pending", "running", "completed", "failed", "all"]), default="all")
@click.pass_context
def task_list(ctx: click.Context, status: str) -> None:
"""List all tasks."""
manager = TaskManager()
manager.load_tasks()
tasks = manager.list_tasks()
if not tasks:
console.print("[yellow]No tasks found. Create one with 'debai task create'[/yellow]")
return
table = Table(
title="[bold]Tasks[/bold]",
box=box.ROUNDED,
show_header=True,
)
table.add_column("ID", style="cyan")
table.add_column("Name")
table.add_column("Type")
table.add_column("Priority")
table.add_column("Status")
for t in tasks:
status_icon = {
"pending": "[dim]○ Pending[/dim]",
"scheduled": "[blue]◐ Scheduled[/blue]",
"running": "[yellow]● Running[/yellow]",
"completed": "[green]✓ Completed[/green]",
"failed": "[red]✗ Failed[/red]",
"cancelled": "[dim]✗ Cancelled[/dim]",
}.get(t.status.value, t.status.value)
priority_style = {
"low": "[dim]Low[/dim]",
"normal": "Normal",
"high": "[yellow]High[/yellow]",
"critical": "[red bold]Critical[/red bold]",
}.get(t.config.priority, t.config.priority)
table.add_row(
t.id,
t.name,
t.config.task_type,
priority_style,
status_icon,
)
console.print(table)
@task.command("create")
@click.option("-n", "--name", prompt="Task name", help="Name for the task")
@click.option("-c", "--command", prompt="Command to run", help="Shell command to execute")
@click.option("-p", "--priority",
type=click.Choice(["low", "normal", "high", "critical"]),
default="normal", help="Task priority")
@click.option("--template", help="Use a predefined template")
@click.pass_context
def task_create(
ctx: click.Context,
name: str,
command: str,
priority: str,
template: Optional[str],
) -> None:
"""Create a new task."""
if template:
config = get_task_template(template)
if not config:
console.print(f"[red]Template '{template}' not found[/red]")
console.print(f"Available templates: {', '.join(list_task_templates())}")
return
config.name = name
else:
config = TaskConfig(
name=name,
command=command,
priority=TaskPriority(priority),
)
manager = TaskManager()
async def create():
return await manager.create_task(config)
task = asyncio.run(create())
console.print(f"\n[green]✓ Task created successfully![/green]")
console.print(f" ID: [cyan]{task.id}[/cyan]")
console.print(f" Name: {task.name}")
console.print(f"\nRun with: [bold]debai task run {task.id}[/bold]")
@task.command("run")
@click.argument("task_id")
@click.pass_context
def task_run(ctx: click.Context, task_id: str) -> None:
"""Run a task."""
manager = TaskManager()
manager.load_tasks()
t = manager.get_task(task_id)
if not t:
console.print(f"[red]Task '{task_id}' not found[/red]")
return
async def run():
return await t.execute()
console.print(f"[bold]Running task: {t.name}[/bold]\n")
result = asyncio.run(run())
if result.success:
console.print(f"[green]✓ Task completed successfully[/green]")
if result.stdout:
console.print(Panel(result.stdout, title="Output", border_style="green"))
else:
console.print(f"[red]✗ Task failed[/red]")
if result.stderr:
console.print(Panel(result.stderr, title="Error", border_style="red"))
console.print(f"\n[dim]Duration: {result.duration_seconds:.2f}s[/dim]")
@task.command("templates")
def task_templates() -> None:
"""List available task templates."""
templates = list_task_templates()
table = Table(
title="[bold]Task Templates[/bold]",
box=box.ROUNDED,
show_header=True,
)
table.add_column("Template")
table.add_column("Description")
table.add_column("Priority")
for name in templates:
config = get_task_template(name)
if config:
table.add_row(name, config.description, config.priority)
console.print(table)
console.print("\nUse with: [bold]debai task create --template <name>[/bold]")
# ============================================================================
# Generate Commands
# ============================================================================
@cli.group()
def generate() -> None:
"""Generate distribution images and configurations."""
pass
@generate.command("iso")
@click.option("-o", "--output", default="debai.iso", help="Output ISO file path")
@click.option("--base", default="debian", help="Base distribution")
@click.option("--include-agents", is_flag=True, help="Include configured agents")
@click.pass_context
def generate_iso(ctx: click.Context, output: str, base: str, include_agents: bool) -> None:
"""Generate a bootable ISO image."""
from debai.generators.iso import ISOGenerator
console.print(Panel(
f"[bold]Generating ISO Image[/bold]\n\n"
f"Output: {output}\n"
f"Base: {base}\n"
f"Include agents: {include_agents}",
title="ISO Generation",
border_style="cyan",
))
generator = ISOGenerator(
output_path=Path(output),
base_distro=base,
include_agents=include_agents,
)
async def gen():
return await generator.generate()
with Progress(
SpinnerColumn(),
TextColumn("[progress.description]{task.description}"),
console=console,
) as progress:
task = progress.add_task("Generating ISO...", total=None)
result = asyncio.run(gen())
if result["success"]:
console.print(f"\n[green]✓ ISO generated: {output}[/green]")
console.print(f" Size: {result['size_mb']:.1f} MB")
else:
console.print(f"\n[red]✗ Failed to generate ISO[/red]")
if result.get("error"):
console.print(f" Error: {result['error']}")
@generate.command("qcow2")
@click.option("-o", "--output", default="debai.qcow2", help="Output QCOW2 file path")
@click.option("--size", default="20G", help="Disk size")
@click.option("--base", default="debian", help="Base distribution")
@click.pass_context
def generate_qcow2(ctx: click.Context, output: str, size: str, base: str) -> None:
"""Generate a QCOW2 image for QEMU."""
from debai.generators.qcow2 import QCOW2Generator
console.print(Panel(
f"[bold]Generating QCOW2 Image[/bold]\n\n"
f"Output: {output}\n"
f"Size: {size}\n"
f"Base: {base}",
title="QCOW2 Generation",
border_style="cyan",
))
generator = QCOW2Generator(
output_path=Path(output),
disk_size=size,
base_distro=base,
)
async def gen():
return await generator.generate()
with Progress(
SpinnerColumn(),
TextColumn("[progress.description]{task.description}"),
console=console,
) as progress:
task = progress.add_task("Generating QCOW2...", total=None)
result = asyncio.run(gen())
if result["success"]:
console.print(f"\n[green]✓ QCOW2 generated: {output}[/green]")
console.print(f" Size: {result['size_mb']:.1f} MB")
else:
console.print(f"\n[red]✗ Failed to generate QCOW2[/red]")
if result.get("error"):
console.print(f" Error: {result['error']}")
@generate.command("compose")
@click.option("-o", "--output", default="docker-compose.yml", help="Output file path")
@click.option("--include-gui", is_flag=True, help="Include GUI service")
@click.pass_context
def generate_compose(ctx: click.Context, output: str, include_gui: bool) -> None:
"""Generate a Docker Compose configuration."""
from debai.generators.compose import ComposeGenerator
generator = ComposeGenerator(
output_path=Path(output),
include_gui=include_gui,
)
result = generator.generate()
if result["success"]:
console.print(f"[green]✓ Docker Compose generated: {output}[/green]")
console.print("\nStart with: [bold]docker compose up -d[/bold]")
else:
console.print(f"[red]✗ Failed to generate Docker Compose[/red]")
# ============================================================================
# Init Command
# ============================================================================
@cli.command()
@click.option("--full", is_flag=True, help="Full initialization with model pull")
@click.pass_context
def init(ctx: click.Context, full: bool) -> None:
"""Initialize Debai environment."""
print_banner()
console.print("\n[bold cyan]🚀 Initializing Debai...[/bold cyan]\n")
# Create configuration directories
config_dir = Path.home() / ".config" / "debai"
dirs = [
config_dir,
config_dir / "agents",
config_dir / "models",
config_dir / "tasks",
Path.home() / ".local" / "share" / "debai",
]
for d in dirs:
d.mkdir(parents=True, exist_ok=True)
console.print(f" [green]✓[/green] Created {d}")
# Check dependencies
console.print("\n[bold]Checking dependencies...[/bold]\n")
deps = check_dependencies()
missing = [d for d, available in deps.items() if not available]
if missing:
console.print(f"[yellow]⚠ Missing dependencies: {', '.join(missing)}[/yellow]")
console.print("\nInstall with your package manager:")
console.print(" [dim]sudo apt install docker.io qemu-utils genisoimage[/dim]")
else:
console.print(" [green]✓[/green] All dependencies available")
if full:
# Pull recommended model
console.print("\n[bold]Pulling recommended model...[/bold]\n")
manager = ModelManager()
config = get_recommended_model("general")
if config:
async def pull():
m = await manager.add_model(config)
return await m.pull()
with Progress(
SpinnerColumn(),
TextColumn("[progress.description]{task.description}"),
console=console,
) as progress:
progress.add_task(f"Pulling {config.id}...", total=None)
asyncio.run(pull())
console.print("\n[bold green]✓ Debai initialized successfully![/bold green]")
console.print("\nNext steps:")
console.print(" 1. Create an agent: [bold]debai agent create[/bold]")
console.print(" 2. Pull a model: [bold]debai model pull llama3.2:3b[/bold]")
console.print(" 3. Start the GUI: [bold]debai-gui[/bold]")
# ============================================================================
# Monitor Command
# ============================================================================
@cli.command()
@click.option("-i", "--interval", default=2.0, help="Update interval in seconds")
@click.pass_context
def monitor(ctx: click.Context, interval: float) -> None:
"""Monitor system resources in real-time."""
from rich.live import Live
from rich.layout import Layout
console.print("[bold]Starting resource monitor...[/bold]")
console.print("[dim]Press Ctrl+C to exit[/dim]\n")
monitor = ResourceMonitor(interval_seconds=interval)
def create_display() -> Table:
snapshot = monitor.get_latest()
if not snapshot:
return Table()
table = Table(box=box.ROUNDED, show_header=False)
table.add_column("Metric", style="bold")
table.add_column("Value")
table.add_row("CPU", f"{snapshot['cpu_percent']:.1f}%")
table.add_row("Memory", f"{snapshot['memory_percent']:.1f}%")
table.add_row("Load (1m)", f"{snapshot['load_1min']:.2f}")
table.add_row("Load (5m)", f"{snapshot['load_5min']:.2f}")
table.add_row("Load (15m)", f"{snapshot['load_15min']:.2f}")
return table
async def run_monitor():
await monitor.start()
try:
with Live(create_display(), console=console, refresh_per_second=1) as live:
while True:
await asyncio.sleep(interval)
live.update(create_display())
except KeyboardInterrupt:
pass
finally:
await monitor.stop()
asyncio.run(run_monitor())
# ============================================================================
# Entry Point
# ============================================================================
def main() -> None:
"""Main entry point."""
try:
cli()
except KeyboardInterrupt:
console.print("\n[yellow]Interrupted[/yellow]")
sys.exit(1)
except Exception as e:
console.print(f"[red]Error: {e}[/red]")
sys.exit(1)
if __name__ == "__main__":
main()

22
src/debai/core/__init__.py Archivo normal
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"""
Core module for Debai - Contains the main business logic.
"""
from debai.core.agent import Agent, AgentConfig, AgentManager
from debai.core.model import Model, ModelConfig, ModelManager
from debai.core.task import Task, TaskConfig, TaskManager
from debai.core.system import SystemInfo, ResourceMonitor
__all__ = [
"Agent",
"AgentConfig",
"AgentManager",
"Model",
"ModelConfig",
"ModelManager",
"Task",
"TaskConfig",
"TaskManager",
"SystemInfo",
"ResourceMonitor",
]

602
src/debai/core/agent.py Archivo normal
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"""
Agent management module for Debai.
This module provides classes and utilities for creating, managing, and
interacting with AI agents using the cagent framework.
"""
from __future__ import annotations
import asyncio
import json
import logging
import os
import subprocess
import uuid
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
from pathlib import Path
from typing import Any, Callable, Optional
import yaml
from pydantic import BaseModel, Field
logger = logging.getLogger(__name__)
class AgentStatus(str, Enum):
"""Agent status enumeration."""
STOPPED = "stopped"
STARTING = "starting"
RUNNING = "running"
PAUSED = "paused"
ERROR = "error"
WAITING = "waiting"
class AgentType(str, Enum):
"""Types of agents available."""
SYSTEM = "system" # System maintenance tasks
PACKAGE = "package" # Package management
CONFIG = "config" # Configuration management
RESOURCE = "resource" # Resource monitoring
SECURITY = "security" # Security tasks
BACKUP = "backup" # Backup management
NETWORK = "network" # Network configuration
CUSTOM = "custom" # User-defined agents
class AgentCapability(str, Enum):
"""Agent capabilities."""
READ_SYSTEM = "read_system"
WRITE_SYSTEM = "write_system"
EXECUTE_COMMANDS = "execute_commands"
NETWORK_ACCESS = "network_access"
FILE_ACCESS = "file_access"
PACKAGE_INSTALL = "package_install"
SERVICE_CONTROL = "service_control"
USER_INTERACTION = "user_interaction"
class AgentConfig(BaseModel):
"""Configuration for an AI agent."""
id: str = Field(default_factory=lambda: str(uuid.uuid4())[:8])
name: str = Field(..., min_length=1, max_length=64)
description: str = Field(default="")
agent_type: AgentType = Field(default=AgentType.CUSTOM)
model_id: str = Field(..., description="ID of the model to use")
capabilities: list[AgentCapability] = Field(default_factory=list)
# Execution settings
auto_start: bool = Field(default=False)
interactive: bool = Field(default=True)
max_retries: int = Field(default=3, ge=0, le=10)
timeout_seconds: int = Field(default=300, ge=10, le=3600)
# Resource limits
max_memory_mb: int = Field(default=512, ge=64, le=8192)
max_cpu_percent: float = Field(default=50.0, ge=1.0, le=100.0)
# Scheduling
schedule_cron: Optional[str] = Field(default=None)
run_on_boot: bool = Field(default=False)
# Environment
environment: dict[str, str] = Field(default_factory=dict)
working_directory: str = Field(default="/tmp/debai")
# Instructions
system_prompt: str = Field(
default="You are a helpful AI assistant managing a GNU/Linux system."
)
allowed_commands: list[str] = Field(default_factory=list)
denied_commands: list[str] = Field(
default_factory=lambda: ["rm -rf /", "dd if=/dev/zero", ":(){ :|:& };:"]
)
# Metadata
created_at: datetime = Field(default_factory=datetime.now)
updated_at: datetime = Field(default_factory=datetime.now)
tags: list[str] = Field(default_factory=list)
class Config:
use_enum_values = True
class AgentMessage(BaseModel):
"""Message exchanged with an agent."""
id: str = Field(default_factory=lambda: str(uuid.uuid4()))
role: str = Field(..., pattern="^(user|assistant|system)$")
content: str
timestamp: datetime = Field(default_factory=datetime.now)
metadata: dict[str, Any] = Field(default_factory=dict)
class Agent:
"""
AI Agent that can perform system tasks autonomously.
This class wraps the cagent framework to provide a high-level interface
for creating and managing AI agents.
"""
def __init__(self, config: AgentConfig):
self.config = config
self.status = AgentStatus.STOPPED
self.process: Optional[subprocess.Popen] = None
self.message_history: list[AgentMessage] = []
self._callbacks: dict[str, list[Callable]] = {
"on_start": [],
"on_stop": [],
"on_message": [],
"on_error": [],
"on_task_complete": [],
}
self._lock = asyncio.Lock()
@property
def id(self) -> str:
return self.config.id
@property
def name(self) -> str:
return self.config.name
def on(self, event: str, callback: Callable) -> None:
"""Register an event callback."""
if event in self._callbacks:
self._callbacks[event].append(callback)
def _emit(self, event: str, *args, **kwargs) -> None:
"""Emit an event to all registered callbacks."""
for callback in self._callbacks.get(event, []):
try:
callback(*args, **kwargs)
except Exception as e:
logger.error(f"Error in callback for {event}: {e}")
async def start(self) -> bool:
"""Start the agent."""
async with self._lock:
if self.status == AgentStatus.RUNNING:
logger.warning(f"Agent {self.name} is already running")
return True
try:
self.status = AgentStatus.STARTING
logger.info(f"Starting agent {self.name}...")
# Create working directory
work_dir = Path(self.config.working_directory)
work_dir.mkdir(parents=True, exist_ok=True)
# Generate agent configuration for cagent
agent_config_path = work_dir / f"agent_{self.id}.yaml"
self._write_cagent_config(agent_config_path)
# Start cagent process
cmd = [
"cagent",
"--config", str(agent_config_path),
"--model", self.config.model_id,
"--interactive" if self.config.interactive else "--daemon",
]
self.process = subprocess.Popen(
cmd,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
cwd=str(work_dir),
env={**os.environ, **self.config.environment},
)
self.status = AgentStatus.RUNNING
self._emit("on_start", self)
logger.info(f"Agent {self.name} started successfully")
return True
except Exception as e:
self.status = AgentStatus.ERROR
self._emit("on_error", self, e)
logger.error(f"Failed to start agent {self.name}: {e}")
return False
async def stop(self) -> bool:
"""Stop the agent."""
async with self._lock:
if self.status == AgentStatus.STOPPED:
return True
try:
if self.process:
self.process.terminate()
try:
self.process.wait(timeout=10)
except subprocess.TimeoutExpired:
self.process.kill()
self.process.wait()
self.status = AgentStatus.STOPPED
self._emit("on_stop", self)
logger.info(f"Agent {self.name} stopped")
return True
except Exception as e:
self._emit("on_error", self, e)
logger.error(f"Failed to stop agent {self.name}: {e}")
return False
async def send_message(self, content: str) -> Optional[AgentMessage]:
"""Send a message to the agent and wait for response."""
if self.status != AgentStatus.RUNNING:
logger.error(f"Agent {self.name} is not running")
return None
try:
# Record user message
user_msg = AgentMessage(role="user", content=content)
self.message_history.append(user_msg)
# Send to agent process
if self.process and self.process.stdin:
self.process.stdin.write(f"{content}\n".encode())
self.process.stdin.flush()
# Read response
if self.process and self.process.stdout:
response = self.process.stdout.readline().decode().strip()
assistant_msg = AgentMessage(role="assistant", content=response)
self.message_history.append(assistant_msg)
self._emit("on_message", self, assistant_msg)
return assistant_msg
return None
except Exception as e:
logger.error(f"Error sending message to agent {self.name}: {e}")
return None
async def execute_task(self, task_description: str) -> dict[str, Any]:
"""Execute a task and return the result."""
result = {
"success": False,
"output": "",
"error": None,
"duration_seconds": 0,
}
start_time = datetime.now()
try:
response = await self.send_message(
f"Execute the following task: {task_description}"
)
if response:
result["success"] = True
result["output"] = response.content
self._emit("on_task_complete", self, result)
except Exception as e:
result["error"] = str(e)
self._emit("on_error", self, e)
result["duration_seconds"] = (datetime.now() - start_time).total_seconds()
return result
def _write_cagent_config(self, path: Path) -> None:
"""Write cagent configuration file."""
config = {
"agent": {
"name": self.config.name,
"description": self.config.description,
"type": self.config.agent_type,
},
"model": {
"id": self.config.model_id,
"provider": "docker-model",
},
"capabilities": list(self.config.capabilities),
"system_prompt": self.config.system_prompt,
"limits": {
"max_memory_mb": self.config.max_memory_mb,
"max_cpu_percent": self.config.max_cpu_percent,
"timeout_seconds": self.config.timeout_seconds,
},
"security": {
"allowed_commands": self.config.allowed_commands,
"denied_commands": self.config.denied_commands,
},
}
with open(path, "w") as f:
yaml.dump(config, f, default_flow_style=False)
def to_dict(self) -> dict[str, Any]:
"""Convert agent to dictionary."""
return {
"id": self.id,
"name": self.name,
"status": self.status.value,
"config": self.config.model_dump(),
"message_count": len(self.message_history),
}
def __repr__(self) -> str:
return f"Agent(id={self.id}, name={self.name}, status={self.status.value})"
class AgentManager:
"""
Manager for multiple AI agents.
Provides functionality to create, start, stop, and manage multiple agents.
"""
def __init__(self, config_dir: Optional[Path] = None):
self.config_dir = config_dir or Path.home() / ".config" / "debai" / "agents"
self.config_dir.mkdir(parents=True, exist_ok=True)
self.agents: dict[str, Agent] = {}
self._lock = asyncio.Lock()
async def create_agent(self, config: AgentConfig) -> Agent:
"""Create a new agent."""
async with self._lock:
if config.id in self.agents:
raise ValueError(f"Agent with id {config.id} already exists")
agent = Agent(config)
self.agents[config.id] = agent
# Save configuration
self._save_agent_config(agent)
logger.info(f"Created agent: {agent.name}")
return agent
def get_agent(self, agent_id: str) -> Optional[Agent]:
"""Get an agent by ID."""
return self.agents.get(agent_id)
def list_agents(
self,
status: Optional[AgentStatus] = None,
agent_type: Optional[AgentType] = None,
) -> list[Agent]:
"""List agents with optional filtering."""
agents = list(self.agents.values())
if status:
agents = [a for a in agents if a.status == status]
if agent_type:
agents = [a for a in agents if a.config.agent_type == agent_type]
return agents
async def start_agent(self, agent_id: str) -> bool:
"""Start an agent by ID."""
agent = self.get_agent(agent_id)
if agent:
return await agent.start()
return False
async def stop_agent(self, agent_id: str) -> bool:
"""Stop an agent by ID."""
agent = self.get_agent(agent_id)
if agent:
return await agent.stop()
return False
async def delete_agent(self, agent_id: str) -> bool:
"""Delete an agent."""
async with self._lock:
agent = self.agents.get(agent_id)
if not agent:
return False
# Stop if running
await agent.stop()
# Remove configuration
config_path = self.config_dir / f"{agent_id}.yaml"
if config_path.exists():
config_path.unlink()
del self.agents[agent_id]
logger.info(f"Deleted agent: {agent_id}")
return True
async def start_all(self, auto_start_only: bool = True) -> dict[str, bool]:
"""Start all agents (optionally only auto-start ones)."""
results = {}
for agent_id, agent in self.agents.items():
if not auto_start_only or agent.config.auto_start:
results[agent_id] = await agent.start()
return results
async def stop_all(self) -> dict[str, bool]:
"""Stop all running agents."""
results = {}
for agent_id, agent in self.agents.items():
if agent.status == AgentStatus.RUNNING:
results[agent_id] = await agent.stop()
return results
def load_agents(self) -> int:
"""Load agents from configuration directory."""
count = 0
for config_file in self.config_dir.glob("*.yaml"):
try:
with open(config_file) as f:
data = yaml.safe_load(f)
config = AgentConfig(**data)
agent = Agent(config)
self.agents[config.id] = agent
count += 1
except Exception as e:
logger.error(f"Failed to load agent from {config_file}: {e}")
logger.info(f"Loaded {count} agents from {self.config_dir}")
return count
def save_agents(self) -> int:
"""Save all agent configurations."""
count = 0
for agent in self.agents.values():
try:
self._save_agent_config(agent)
count += 1
except Exception as e:
logger.error(f"Failed to save agent {agent.id}: {e}")
return count
def _save_agent_config(self, agent: Agent) -> None:
"""Save agent configuration to file."""
config_path = self.config_dir / f"{agent.id}.yaml"
with open(config_path, "w") as f:
yaml.dump(agent.config.model_dump(), f, default_flow_style=False)
def get_statistics(self) -> dict[str, Any]:
"""Get agent statistics."""
total = len(self.agents)
by_status = {}
by_type = {}
for agent in self.agents.values():
status = agent.status.value
agent_type = agent.config.agent_type
by_status[status] = by_status.get(status, 0) + 1
by_type[agent_type] = by_type.get(agent_type, 0) + 1
return {
"total": total,
"by_status": by_status,
"by_type": by_type,
}
# Predefined agent templates
AGENT_TEMPLATES = {
"package_updater": AgentConfig(
name="Package Updater",
description="Automatically updates system packages",
agent_type=AgentType.PACKAGE,
model_id="llama3.2:3b",
capabilities=[
AgentCapability.READ_SYSTEM,
AgentCapability.EXECUTE_COMMANDS,
AgentCapability.PACKAGE_INSTALL,
],
system_prompt="""You are a package management agent for a GNU/Linux system.
Your role is to:
1. Check for available package updates
2. Review update changelogs for security implications
3. Apply updates safely during low-usage periods
4. Report any issues or conflicts
Always prioritize security updates and be cautious with major version upgrades.""",
allowed_commands=["apt", "apt-get", "dpkg", "snap", "flatpak"],
schedule_cron="0 3 * * *", # 3 AM daily
),
"config_manager": AgentConfig(
name="Configuration Manager",
description="Manages application configurations",
agent_type=AgentType.CONFIG,
model_id="llama3.2:3b",
capabilities=[
AgentCapability.READ_SYSTEM,
AgentCapability.FILE_ACCESS,
AgentCapability.USER_INTERACTION,
],
system_prompt="""You are a configuration management agent.
Your role is to:
1. Monitor configuration files for changes
2. Validate configurations against best practices
3. Suggest optimizations
4. Backup configurations before changes
5. Help users with configuration questions
Always create backups before modifying any configuration.""",
),
"resource_monitor": AgentConfig(
name="Resource Monitor",
description="Monitors and optimizes system resources",
agent_type=AgentType.RESOURCE,
model_id="llama3.2:3b",
capabilities=[
AgentCapability.READ_SYSTEM,
AgentCapability.EXECUTE_COMMANDS,
AgentCapability.SERVICE_CONTROL,
],
system_prompt="""You are a resource monitoring agent.
Your role is to:
1. Monitor CPU, memory, disk, and network usage
2. Identify resource-hungry processes
3. Suggest optimizations
4. Alert on critical thresholds
5. Perform automatic cleanup of temporary files
Never terminate critical system processes without explicit permission.""",
schedule_cron="*/15 * * * *", # Every 15 minutes
),
"security_guard": AgentConfig(
name="Security Guard",
description="Monitors system security",
agent_type=AgentType.SECURITY,
model_id="llama3.2:3b",
capabilities=[
AgentCapability.READ_SYSTEM,
AgentCapability.EXECUTE_COMMANDS,
AgentCapability.NETWORK_ACCESS,
],
system_prompt="""You are a security monitoring agent.
Your role is to:
1. Monitor system logs for suspicious activity
2. Check for unauthorized access attempts
3. Verify file integrity
4. Monitor open ports and network connections
5. Alert on security issues
Never expose sensitive information in logs or reports.""",
interactive=True,
),
"backup_agent": AgentConfig(
name="Backup Manager",
description="Manages system backups",
agent_type=AgentType.BACKUP,
model_id="llama3.2:3b",
capabilities=[
AgentCapability.READ_SYSTEM,
AgentCapability.FILE_ACCESS,
AgentCapability.EXECUTE_COMMANDS,
],
system_prompt="""You are a backup management agent.
Your role is to:
1. Create regular backups of important data
2. Verify backup integrity
3. Manage backup retention policies
4. Perform restore operations when needed
5. Monitor backup storage usage
Always verify backups after creation.""",
schedule_cron="0 2 * * *", # 2 AM daily
),
}
def get_agent_template(template_name: str) -> Optional[AgentConfig]:
"""Get a predefined agent template."""
return AGENT_TEMPLATES.get(template_name)
def list_agent_templates() -> list[str]:
"""List available agent templates."""
return list(AGENT_TEMPLATES.keys())

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src/debai/core/model.py Archivo normal
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"""
Model management module for Debai.
This module provides classes and utilities for managing AI models
using Docker Model Runner.
"""
from __future__ import annotations
import asyncio
import json
import logging
import re
import subprocess
from dataclasses import dataclass
from datetime import datetime
from enum import Enum
from pathlib import Path
from typing import Any, Optional
import yaml
from pydantic import BaseModel, Field
logger = logging.getLogger(__name__)
class ModelStatus(str, Enum):
"""Model status enumeration."""
NOT_PULLED = "not_pulled"
PULLING = "pulling"
READY = "ready"
LOADING = "loading"
LOADED = "loaded"
ERROR = "error"
class ModelProvider(str, Enum):
"""Model providers."""
DOCKER_MODEL = "docker-model"
OLLAMA = "ollama"
LOCAL = "local"
class ModelCapability(str, Enum):
"""Model capabilities."""
TEXT_GENERATION = "text_generation"
CODE_GENERATION = "code_generation"
CHAT = "chat"
EMBEDDING = "embedding"
VISION = "vision"
FUNCTION_CALLING = "function_calling"
class ModelConfig(BaseModel):
"""Configuration for an AI model."""
id: str = Field(..., min_length=1)
name: str = Field(..., min_length=1)
provider: ModelProvider = Field(default=ModelProvider.DOCKER_MODEL)
description: str = Field(default="")
# Model specifications
parameter_count: str = Field(default="") # e.g., "7B", "13B"
context_length: int = Field(default=4096, ge=512, le=131072)
quantization: str = Field(default="") # e.g., "Q4_K_M", "Q8_0"
# Capabilities
capabilities: list[ModelCapability] = Field(default_factory=list)
# Runtime settings
gpu_layers: int = Field(default=0, ge=0)
threads: int = Field(default=4, ge=1, le=64)
batch_size: int = Field(default=512, ge=1, le=4096)
# Generation defaults
temperature: float = Field(default=0.7, ge=0.0, le=2.0)
top_p: float = Field(default=0.9, ge=0.0, le=1.0)
top_k: int = Field(default=40, ge=0, le=100)
repeat_penalty: float = Field(default=1.1, ge=1.0, le=2.0)
# Metadata
size_bytes: int = Field(default=0, ge=0)
created_at: datetime = Field(default_factory=datetime.now)
tags: list[str] = Field(default_factory=list)
class Config:
use_enum_values = True
class Model:
"""
AI Model wrapper for Docker Model Runner.
Provides a high-level interface for managing and using AI models.
"""
def __init__(self, config: ModelConfig):
self.config = config
self.status = ModelStatus.NOT_PULLED
self._lock = asyncio.Lock()
@property
def id(self) -> str:
return self.config.id
@property
def name(self) -> str:
return self.config.name
@property
def is_ready(self) -> bool:
return self.status in (ModelStatus.READY, ModelStatus.LOADED)
async def pull(self, progress_callback: Optional[callable] = None) -> bool:
"""Pull the model from Docker Model Runner."""
async with self._lock:
if self.status == ModelStatus.READY:
return True
try:
self.status = ModelStatus.PULLING
logger.info(f"Pulling model {self.id}...")
# Use docker model pull
process = await asyncio.create_subprocess_exec(
"docker", "model", "pull", self.id,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
stdout, stderr = await process.communicate()
if process.returncode == 0:
self.status = ModelStatus.READY
logger.info(f"Model {self.id} pulled successfully")
return True
else:
self.status = ModelStatus.ERROR
logger.error(f"Failed to pull model: {stderr.decode()}")
return False
except Exception as e:
self.status = ModelStatus.ERROR
logger.error(f"Error pulling model {self.id}: {e}")
return False
async def load(self) -> bool:
"""Load the model into memory."""
if self.status not in (ModelStatus.READY, ModelStatus.LOADED):
logger.error(f"Model {self.id} is not ready")
return False
try:
self.status = ModelStatus.LOADING
# Start docker model serve
process = await asyncio.create_subprocess_exec(
"docker", "model", "serve", self.id,
"--threads", str(self.config.threads),
"--ctx-size", str(self.config.context_length),
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
self.status = ModelStatus.LOADED
logger.info(f"Model {self.id} loaded")
return True
except Exception as e:
self.status = ModelStatus.ERROR
logger.error(f"Error loading model {self.id}: {e}")
return False
async def generate(
self,
prompt: str,
max_tokens: int = 512,
temperature: Optional[float] = None,
stop_sequences: Optional[list[str]] = None,
) -> str:
"""Generate text using the model."""
if not self.is_ready:
raise RuntimeError(f"Model {self.id} is not ready")
try:
# Build generation request
cmd = [
"docker", "model", "run", self.id,
"--prompt", prompt,
"--max-tokens", str(max_tokens),
"--temperature", str(temperature or self.config.temperature),
]
if stop_sequences:
for seq in stop_sequences:
cmd.extend(["--stop", seq])
process = await asyncio.create_subprocess_exec(
*cmd,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
stdout, stderr = await process.communicate()
if process.returncode == 0:
return stdout.decode().strip()
else:
raise RuntimeError(f"Generation failed: {stderr.decode()}")
except Exception as e:
logger.error(f"Error generating text: {e}")
raise
async def chat(
self,
messages: list[dict[str, str]],
max_tokens: int = 512,
temperature: Optional[float] = None,
) -> str:
"""Chat with the model."""
if not self.is_ready:
raise RuntimeError(f"Model {self.id} is not ready")
# Format messages for chat
formatted = []
for msg in messages:
role = msg.get("role", "user")
content = msg.get("content", "")
formatted.append(f"{role}: {content}")
prompt = "\n".join(formatted) + "\nassistant:"
return await self.generate(prompt, max_tokens, temperature)
def to_dict(self) -> dict[str, Any]:
"""Convert model to dictionary."""
return {
"id": self.id,
"name": self.name,
"status": self.status.value,
"config": self.config.model_dump(),
}
def __repr__(self) -> str:
return f"Model(id={self.id}, status={self.status.value})"
class ModelManager:
"""
Manager for AI models.
Handles model discovery, pulling, loading, and lifecycle management.
"""
def __init__(self, config_dir: Optional[Path] = None):
self.config_dir = config_dir or Path.home() / ".config" / "debai" / "models"
self.config_dir.mkdir(parents=True, exist_ok=True)
self.models: dict[str, Model] = {}
self._lock = asyncio.Lock()
async def discover_models(self) -> list[ModelConfig]:
"""Discover available models from Docker Model Runner."""
models = []
try:
process = await asyncio.create_subprocess_exec(
"docker", "model", "list", "--format", "json",
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
stdout, stderr = await process.communicate()
if process.returncode == 0:
data = json.loads(stdout.decode())
for item in data:
config = ModelConfig(
id=item.get("name", item.get("id", "")),
name=item.get("name", ""),
size_bytes=item.get("size", 0),
)
models.append(config)
except Exception as e:
logger.error(f"Error discovering models: {e}")
return models
async def add_model(self, config: ModelConfig) -> Model:
"""Add a model to the manager."""
async with self._lock:
if config.id in self.models:
return self.models[config.id]
model = Model(config)
self.models[config.id] = model
# Save configuration
self._save_model_config(model)
logger.info(f"Added model: {model.name}")
return model
def get_model(self, model_id: str) -> Optional[Model]:
"""Get a model by ID."""
return self.models.get(model_id)
def list_models(
self,
status: Optional[ModelStatus] = None,
capability: Optional[ModelCapability] = None,
) -> list[Model]:
"""List models with optional filtering."""
models = list(self.models.values())
if status:
models = [m for m in models if m.status == status]
if capability:
models = [
m for m in models
if capability in m.config.capabilities
]
return models
async def pull_model(
self,
model_id: str,
progress_callback: Optional[callable] = None,
) -> bool:
"""Pull a model by ID."""
model = self.get_model(model_id)
if model:
return await model.pull(progress_callback)
return False
async def remove_model(self, model_id: str) -> bool:
"""Remove a model."""
async with self._lock:
model = self.models.get(model_id)
if not model:
return False
try:
# Remove from Docker Model Runner
process = await asyncio.create_subprocess_exec(
"docker", "model", "rm", model_id,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
await process.communicate()
except Exception as e:
logger.warning(f"Error removing model from runner: {e}")
# Remove configuration
config_path = self.config_dir / f"{model_id.replace(':', '_')}.yaml"
if config_path.exists():
config_path.unlink()
del self.models[model_id]
logger.info(f"Removed model: {model_id}")
return True
def load_models(self) -> int:
"""Load models from configuration directory."""
count = 0
for config_file in self.config_dir.glob("*.yaml"):
try:
with open(config_file) as f:
data = yaml.safe_load(f)
config = ModelConfig(**data)
model = Model(config)
model.status = ModelStatus.READY # Assume ready if configured
self.models[config.id] = model
count += 1
except Exception as e:
logger.error(f"Failed to load model from {config_file}: {e}")
logger.info(f"Loaded {count} models from {self.config_dir}")
return count
def save_models(self) -> int:
"""Save all model configurations."""
count = 0
for model in self.models.values():
try:
self._save_model_config(model)
count += 1
except Exception as e:
logger.error(f"Failed to save model {model.id}: {e}")
return count
def _save_model_config(self, model: Model) -> None:
"""Save model configuration to file."""
config_path = self.config_dir / f"{model.id.replace(':', '_')}.yaml"
with open(config_path, "w") as f:
yaml.dump(model.config.model_dump(), f, default_flow_style=False)
def get_statistics(self) -> dict[str, Any]:
"""Get model statistics."""
total = len(self.models)
by_status = {}
total_size = 0
for model in self.models.values():
status = model.status.value
by_status[status] = by_status.get(status, 0) + 1
total_size += model.config.size_bytes
return {
"total": total,
"by_status": by_status,
"total_size_bytes": total_size,
"total_size_gb": round(total_size / (1024**3), 2),
}
# Recommended models for different use cases
RECOMMENDED_MODELS = {
"general": ModelConfig(
id="llama3.2:3b",
name="Llama 3.2 3B",
description="Balanced model for general tasks",
parameter_count="3B",
context_length=8192,
capabilities=[
ModelCapability.TEXT_GENERATION,
ModelCapability.CHAT,
ModelCapability.CODE_GENERATION,
],
),
"code": ModelConfig(
id="codellama:7b",
name="Code Llama 7B",
description="Specialized for code generation and analysis",
parameter_count="7B",
context_length=16384,
capabilities=[
ModelCapability.CODE_GENERATION,
ModelCapability.TEXT_GENERATION,
],
),
"small": ModelConfig(
id="llama3.2:1b",
name="Llama 3.2 1B",
description="Lightweight model for simple tasks",
parameter_count="1B",
context_length=4096,
capabilities=[
ModelCapability.TEXT_GENERATION,
ModelCapability.CHAT,
],
),
"large": ModelConfig(
id="llama3.1:8b",
name="Llama 3.1 8B",
description="Larger model for complex tasks",
parameter_count="8B",
context_length=16384,
capabilities=[
ModelCapability.TEXT_GENERATION,
ModelCapability.CHAT,
ModelCapability.CODE_GENERATION,
ModelCapability.FUNCTION_CALLING,
],
),
}
def get_recommended_model(use_case: str) -> Optional[ModelConfig]:
"""Get a recommended model for a specific use case."""
return RECOMMENDED_MODELS.get(use_case)
def list_recommended_models() -> list[str]:
"""List available recommended model configurations."""
return list(RECOMMENDED_MODELS.keys())

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"""
System information and resource monitoring module for Debai.
This module provides utilities for gathering system information and
monitoring resource usage.
"""
from __future__ import annotations
import asyncio
import logging
import os
import platform
import subprocess
from dataclasses import dataclass
from datetime import datetime
from pathlib import Path
from typing import Any, Optional
import psutil
logger = logging.getLogger(__name__)
@dataclass
class CPUInfo:
"""CPU information."""
model: str
cores_physical: int
cores_logical: int
frequency_mhz: float
usage_percent: float
temperature: Optional[float] = None
@dataclass
class MemoryInfo:
"""Memory information."""
total_bytes: int
available_bytes: int
used_bytes: int
percent_used: float
swap_total_bytes: int
swap_used_bytes: int
swap_percent_used: float
@dataclass
class DiskInfo:
"""Disk information for a partition."""
device: str
mountpoint: str
filesystem: str
total_bytes: int
used_bytes: int
free_bytes: int
percent_used: float
@dataclass
class NetworkInfo:
"""Network interface information."""
interface: str
ip_address: str
mac_address: str
bytes_sent: int
bytes_recv: int
packets_sent: int
packets_recv: int
@dataclass
class ProcessInfo:
"""Process information."""
pid: int
name: str
username: str
cpu_percent: float
memory_percent: float
memory_bytes: int
status: str
created: datetime
class SystemInfo:
"""
Gathers system information.
"""
@staticmethod
def get_hostname() -> str:
"""Get the system hostname."""
return platform.node()
@staticmethod
def get_os_info() -> dict[str, str]:
"""Get operating system information."""
return {
"system": platform.system(),
"release": platform.release(),
"version": platform.version(),
"machine": platform.machine(),
"processor": platform.processor(),
}
@staticmethod
def get_distro_info() -> dict[str, str]:
"""Get Linux distribution information."""
info = {
"name": "",
"version": "",
"codename": "",
"id": "",
}
try:
# Try /etc/os-release first
os_release = Path("/etc/os-release")
if os_release.exists():
for line in os_release.read_text().splitlines():
if "=" in line:
key, value = line.split("=", 1)
value = value.strip('"')
if key == "NAME":
info["name"] = value
elif key == "VERSION_ID":
info["version"] = value
elif key == "VERSION_CODENAME":
info["codename"] = value
elif key == "ID":
info["id"] = value
except Exception as e:
logger.warning(f"Error reading distro info: {e}")
return info
@staticmethod
def get_cpu_info() -> CPUInfo:
"""Get CPU information."""
freq = psutil.cpu_freq()
# Get CPU model
model = ""
try:
with open("/proc/cpuinfo") as f:
for line in f:
if line.startswith("model name"):
model = line.split(":")[1].strip()
break
except Exception:
model = platform.processor()
# Get temperature if available
temp = None
try:
temps = psutil.sensors_temperatures()
if temps:
for name, entries in temps.items():
if entries:
temp = entries[0].current
break
except Exception:
pass
return CPUInfo(
model=model,
cores_physical=psutil.cpu_count(logical=False) or 1,
cores_logical=psutil.cpu_count(logical=True) or 1,
frequency_mhz=freq.current if freq else 0,
usage_percent=psutil.cpu_percent(interval=0.1),
temperature=temp,
)
@staticmethod
def get_memory_info() -> MemoryInfo:
"""Get memory information."""
mem = psutil.virtual_memory()
swap = psutil.swap_memory()
return MemoryInfo(
total_bytes=mem.total,
available_bytes=mem.available,
used_bytes=mem.used,
percent_used=mem.percent,
swap_total_bytes=swap.total,
swap_used_bytes=swap.used,
swap_percent_used=swap.percent,
)
@staticmethod
def get_disk_info() -> list[DiskInfo]:
"""Get disk information for all partitions."""
disks = []
for partition in psutil.disk_partitions(all=False):
try:
usage = psutil.disk_usage(partition.mountpoint)
disks.append(DiskInfo(
device=partition.device,
mountpoint=partition.mountpoint,
filesystem=partition.fstype,
total_bytes=usage.total,
used_bytes=usage.used,
free_bytes=usage.free,
percent_used=usage.percent,
))
except (PermissionError, OSError):
continue
return disks
@staticmethod
def get_network_info() -> list[NetworkInfo]:
"""Get network interface information."""
interfaces = []
addrs = psutil.net_if_addrs()
stats = psutil.net_io_counters(pernic=True)
for name, addr_list in addrs.items():
if name == "lo":
continue
ip_addr = ""
mac_addr = ""
for addr in addr_list:
if addr.family.name == "AF_INET":
ip_addr = addr.address
elif addr.family.name == "AF_PACKET":
mac_addr = addr.address
io = stats.get(name)
interfaces.append(NetworkInfo(
interface=name,
ip_address=ip_addr,
mac_address=mac_addr,
bytes_sent=io.bytes_sent if io else 0,
bytes_recv=io.bytes_recv if io else 0,
packets_sent=io.packets_sent if io else 0,
packets_recv=io.packets_recv if io else 0,
))
return interfaces
@staticmethod
def get_uptime() -> float:
"""Get system uptime in seconds."""
return datetime.now().timestamp() - psutil.boot_time()
@staticmethod
def get_uptime_string() -> str:
"""Get human-readable uptime string."""
uptime = SystemInfo.get_uptime()
days = int(uptime // 86400)
hours = int((uptime % 86400) // 3600)
minutes = int((uptime % 3600) // 60)
parts = []
if days > 0:
parts.append(f"{days}d")
if hours > 0:
parts.append(f"{hours}h")
parts.append(f"{minutes}m")
return " ".join(parts)
@staticmethod
def get_load_average() -> tuple[float, float, float]:
"""Get system load average (1, 5, 15 minutes)."""
return os.getloadavg()
@staticmethod
def get_logged_users() -> list[str]:
"""Get list of logged-in users."""
users = []
for user in psutil.users():
users.append(f"{user.name}@{user.terminal}")
return users
@staticmethod
def get_summary() -> dict[str, Any]:
"""Get a summary of system information."""
return {
"hostname": SystemInfo.get_hostname(),
"os": SystemInfo.get_os_info(),
"distro": SystemInfo.get_distro_info(),
"cpu": SystemInfo.get_cpu_info().__dict__,
"memory": SystemInfo.get_memory_info().__dict__,
"uptime": SystemInfo.get_uptime_string(),
"load_average": SystemInfo.get_load_average(),
}
class ResourceMonitor:
"""
Monitors system resources continuously.
"""
def __init__(
self,
interval_seconds: float = 5.0,
history_size: int = 100,
):
self.interval = interval_seconds
self.history_size = history_size
self.history: list[dict[str, Any]] = []
self._running = False
self._task: Optional[asyncio.Task] = None
self._callbacks: list[callable] = []
# Thresholds
self.thresholds = {
"cpu_percent": 80.0,
"memory_percent": 85.0,
"disk_percent": 90.0,
"load_1min": psutil.cpu_count() or 1,
}
self._alerts: list[dict[str, Any]] = []
def on_update(self, callback: callable) -> None:
"""Register a callback for updates."""
self._callbacks.append(callback)
def set_threshold(self, metric: str, value: float) -> None:
"""Set a threshold for a metric."""
self.thresholds[metric] = value
async def start(self) -> None:
"""Start the resource monitor."""
if self._running:
return
self._running = True
self._task = asyncio.create_task(self._monitor_loop())
logger.info("Resource monitor started")
async def stop(self) -> None:
"""Stop the resource monitor."""
self._running = False
if self._task:
self._task.cancel()
try:
await self._task
except asyncio.CancelledError:
pass
logger.info("Resource monitor stopped")
async def _monitor_loop(self) -> None:
"""Main monitoring loop."""
while self._running:
try:
snapshot = self._take_snapshot()
self._add_to_history(snapshot)
self._check_thresholds(snapshot)
# Notify callbacks
for callback in self._callbacks:
try:
callback(snapshot)
except Exception as e:
logger.error(f"Error in monitor callback: {e}")
await asyncio.sleep(self.interval)
except asyncio.CancelledError:
break
except Exception as e:
logger.error(f"Error in monitor loop: {e}")
await asyncio.sleep(1)
def _take_snapshot(self) -> dict[str, Any]:
"""Take a resource snapshot."""
cpu = psutil.cpu_percent(interval=0.1)
mem = psutil.virtual_memory()
load = os.getloadavg()
# Get top processes by CPU
top_cpu = []
for proc in sorted(
psutil.process_iter(['pid', 'name', 'cpu_percent', 'memory_percent']),
key=lambda p: p.info.get('cpu_percent', 0) or 0,
reverse=True,
)[:5]:
try:
info = proc.info
top_cpu.append({
"pid": info['pid'],
"name": info['name'],
"cpu_percent": info['cpu_percent'],
"memory_percent": info['memory_percent'],
})
except (psutil.NoSuchProcess, psutil.AccessDenied):
continue
return {
"timestamp": datetime.now().isoformat(),
"cpu_percent": cpu,
"memory_percent": mem.percent,
"memory_available_mb": mem.available / (1024 * 1024),
"load_1min": load[0],
"load_5min": load[1],
"load_15min": load[2],
"top_processes": top_cpu,
}
def _add_to_history(self, snapshot: dict[str, Any]) -> None:
"""Add a snapshot to history."""
self.history.append(snapshot)
if len(self.history) > self.history_size:
self.history.pop(0)
def _check_thresholds(self, snapshot: dict[str, Any]) -> None:
"""Check thresholds and generate alerts."""
alerts = []
if snapshot["cpu_percent"] > self.thresholds["cpu_percent"]:
alerts.append({
"type": "cpu",
"message": f"CPU usage is {snapshot['cpu_percent']:.1f}%",
"value": snapshot["cpu_percent"],
"threshold": self.thresholds["cpu_percent"],
})
if snapshot["memory_percent"] > self.thresholds["memory_percent"]:
alerts.append({
"type": "memory",
"message": f"Memory usage is {snapshot['memory_percent']:.1f}%",
"value": snapshot["memory_percent"],
"threshold": self.thresholds["memory_percent"],
})
if snapshot["load_1min"] > self.thresholds["load_1min"]:
alerts.append({
"type": "load",
"message": f"Load average is {snapshot['load_1min']:.2f}",
"value": snapshot["load_1min"],
"threshold": self.thresholds["load_1min"],
})
if alerts:
for alert in alerts:
alert["timestamp"] = snapshot["timestamp"]
self._alerts.extend(alerts)
# Keep only recent alerts
if len(self._alerts) > 100:
self._alerts = self._alerts[-100:]
def get_latest(self) -> Optional[dict[str, Any]]:
"""Get the latest snapshot."""
return self.history[-1] if self.history else None
def get_history(self, count: int = 0) -> list[dict[str, Any]]:
"""Get recent history."""
if count <= 0:
return list(self.history)
return list(self.history[-count:])
def get_alerts(self, count: int = 10) -> list[dict[str, Any]]:
"""Get recent alerts."""
return list(self._alerts[-count:])
def get_average(self, metric: str, minutes: int = 5) -> Optional[float]:
"""Get average value of a metric over a time period."""
if not self.history:
return None
# Calculate how many samples to use
samples_per_minute = 60 / self.interval
samples = int(samples_per_minute * minutes)
recent = self.history[-samples:] if samples < len(self.history) else self.history
values = [s.get(metric, 0) for s in recent if metric in s]
return sum(values) / len(values) if values else None
def get_statistics(self) -> dict[str, Any]:
"""Get monitoring statistics."""
if not self.history:
return {}
cpu_values = [s["cpu_percent"] for s in self.history]
mem_values = [s["memory_percent"] for s in self.history]
return {
"samples": len(self.history),
"interval_seconds": self.interval,
"cpu": {
"current": cpu_values[-1],
"average": sum(cpu_values) / len(cpu_values),
"max": max(cpu_values),
"min": min(cpu_values),
},
"memory": {
"current": mem_values[-1],
"average": sum(mem_values) / len(mem_values),
"max": max(mem_values),
"min": min(mem_values),
},
"alerts_count": len(self._alerts),
}
def format_bytes(size: int) -> str:
"""Format bytes to human-readable string."""
for unit in ["B", "KB", "MB", "GB", "TB"]:
if abs(size) < 1024.0:
return f"{size:.1f} {unit}"
size /= 1024.0
return f"{size:.1f} PB"
def get_docker_status() -> dict[str, Any]:
"""Get Docker status."""
result = {
"installed": False,
"running": False,
"version": "",
"containers": 0,
"images": 0,
}
try:
# Check if docker is installed
version = subprocess.run(
["docker", "--version"],
capture_output=True,
text=True,
)
if version.returncode == 0:
result["installed"] = True
result["version"] = version.stdout.strip()
# Check if docker is running
info = subprocess.run(
["docker", "info", "--format", "{{json .}}"],
capture_output=True,
text=True,
)
if info.returncode == 0:
result["running"] = True
import json
data = json.loads(info.stdout)
result["containers"] = data.get("Containers", 0)
result["images"] = data.get("Images", 0)
except Exception as e:
logger.debug(f"Error checking Docker status: {e}")
return result
def check_dependencies() -> dict[str, bool]:
"""Check if required dependencies are available."""
deps = {
"docker": False,
"docker-model": False,
"cagent": False,
"qemu-img": False,
"genisoimage": False,
}
for dep in deps:
try:
result = subprocess.run(
["which", dep],
capture_output=True,
)
deps[dep] = result.returncode == 0
except Exception:
pass
return deps

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"""
Task management module for Debai.
This module provides classes and utilities for creating and managing
automated tasks that agents can execute.
"""
from __future__ import annotations
import asyncio
import json
import logging
import uuid
from datetime import datetime, timedelta
from enum import Enum
from pathlib import Path
from typing import Any, Callable, Optional
import yaml
from pydantic import BaseModel, Field
logger = logging.getLogger(__name__)
class TaskStatus(str, Enum):
"""Task status enumeration."""
PENDING = "pending"
SCHEDULED = "scheduled"
RUNNING = "running"
COMPLETED = "completed"
FAILED = "failed"
CANCELLED = "cancelled"
PAUSED = "paused"
class TaskPriority(str, Enum):
"""Task priority levels."""
LOW = "low"
NORMAL = "normal"
HIGH = "high"
CRITICAL = "critical"
class TaskType(str, Enum):
"""Types of tasks."""
COMMAND = "command" # Execute shell command
SCRIPT = "script" # Run a script file
AGENT = "agent" # Delegate to agent
WORKFLOW = "workflow" # Multi-step workflow
SCHEDULED = "scheduled" # Cron-scheduled task
EVENT = "event" # Event-triggered task
class TaskConfig(BaseModel):
"""Configuration for a task."""
id: str = Field(default_factory=lambda: str(uuid.uuid4())[:8])
name: str = Field(..., min_length=1, max_length=128)
description: str = Field(default="")
task_type: TaskType = Field(default=TaskType.COMMAND)
priority: TaskPriority = Field(default=TaskPriority.NORMAL)
# Execution
command: str = Field(default="")
script_path: str = Field(default="")
agent_id: Optional[str] = Field(default=None)
working_directory: str = Field(default="/tmp")
environment: dict[str, str] = Field(default_factory=dict)
# Scheduling
schedule_cron: Optional[str] = Field(default=None)
schedule_at: Optional[datetime] = Field(default=None)
repeat_count: int = Field(default=0) # 0 = infinite
repeat_interval_minutes: int = Field(default=0)
# Limits
timeout_seconds: int = Field(default=300, ge=1, le=86400)
max_retries: int = Field(default=3, ge=0, le=10)
retry_delay_seconds: int = Field(default=30, ge=1, le=3600)
# Dependencies
depends_on: list[str] = Field(default_factory=list)
blocks: list[str] = Field(default_factory=list)
# Notifications
notify_on_complete: bool = Field(default=False)
notify_on_failure: bool = Field(default=True)
notification_email: Optional[str] = Field(default=None)
# Metadata
created_at: datetime = Field(default_factory=datetime.now)
updated_at: datetime = Field(default_factory=datetime.now)
tags: list[str] = Field(default_factory=list)
class Config:
use_enum_values = True
class TaskResult(BaseModel):
"""Result of a task execution."""
task_id: str
success: bool
exit_code: int = Field(default=0)
stdout: str = Field(default="")
stderr: str = Field(default="")
started_at: datetime
completed_at: datetime
duration_seconds: float
retry_count: int = Field(default=0)
error_message: Optional[str] = Field(default=None)
metadata: dict[str, Any] = Field(default_factory=dict)
class Task:
"""
A task that can be executed by the system or delegated to an agent.
"""
def __init__(self, config: TaskConfig):
self.config = config
self.status = TaskStatus.PENDING
self.current_retry = 0
self.last_result: Optional[TaskResult] = None
self.history: list[TaskResult] = []
self._callbacks: dict[str, list[Callable]] = {
"on_start": [],
"on_complete": [],
"on_failure": [],
"on_retry": [],
}
self._lock = asyncio.Lock()
self._process: Optional[asyncio.subprocess.Process] = None
@property
def id(self) -> str:
return self.config.id
@property
def name(self) -> str:
return self.config.name
def on(self, event: str, callback: Callable) -> None:
"""Register an event callback."""
if event in self._callbacks:
self._callbacks[event].append(callback)
def _emit(self, event: str, *args, **kwargs) -> None:
"""Emit an event to all registered callbacks."""
for callback in self._callbacks.get(event, []):
try:
callback(*args, **kwargs)
except Exception as e:
logger.error(f"Error in callback for {event}: {e}")
async def execute(self) -> TaskResult:
"""Execute the task."""
async with self._lock:
started_at = datetime.now()
self.status = TaskStatus.RUNNING
self._emit("on_start", self)
try:
if self.config.task_type == TaskType.COMMAND:
result = await self._execute_command()
elif self.config.task_type == TaskType.SCRIPT:
result = await self._execute_script()
elif self.config.task_type == TaskType.AGENT:
result = await self._execute_agent()
else:
result = await self._execute_command()
completed_at = datetime.now()
task_result = TaskResult(
task_id=self.id,
success=result["success"],
exit_code=result.get("exit_code", 0),
stdout=result.get("stdout", ""),
stderr=result.get("stderr", ""),
started_at=started_at,
completed_at=completed_at,
duration_seconds=(completed_at - started_at).total_seconds(),
retry_count=self.current_retry,
)
if task_result.success:
self.status = TaskStatus.COMPLETED
self._emit("on_complete", self, task_result)
else:
if self.current_retry < self.config.max_retries:
self.current_retry += 1
self._emit("on_retry", self, self.current_retry)
await asyncio.sleep(self.config.retry_delay_seconds)
return await self.execute()
else:
self.status = TaskStatus.FAILED
self._emit("on_failure", self, task_result)
self.last_result = task_result
self.history.append(task_result)
return task_result
except Exception as e:
completed_at = datetime.now()
task_result = TaskResult(
task_id=self.id,
success=False,
exit_code=-1,
started_at=started_at,
completed_at=completed_at,
duration_seconds=(completed_at - started_at).total_seconds(),
error_message=str(e),
)
self.status = TaskStatus.FAILED
self._emit("on_failure", self, task_result)
self.last_result = task_result
self.history.append(task_result)
return task_result
async def _execute_command(self) -> dict[str, Any]:
"""Execute a shell command."""
try:
self._process = await asyncio.create_subprocess_shell(
self.config.command,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
cwd=self.config.working_directory,
env={**dict(Path("/etc/environment").read_text().split("=")) if Path("/etc/environment").exists() else {}, **self.config.environment},
)
try:
stdout, stderr = await asyncio.wait_for(
self._process.communicate(),
timeout=self.config.timeout_seconds,
)
except asyncio.TimeoutError:
self._process.kill()
await self._process.wait()
return {
"success": False,
"exit_code": -1,
"stderr": "Task timed out",
}
return {
"success": self._process.returncode == 0,
"exit_code": self._process.returncode,
"stdout": stdout.decode() if stdout else "",
"stderr": stderr.decode() if stderr else "",
}
except Exception as e:
return {
"success": False,
"exit_code": -1,
"stderr": str(e),
}
async def _execute_script(self) -> dict[str, Any]:
"""Execute a script file."""
script_path = Path(self.config.script_path)
if not script_path.exists():
return {
"success": False,
"exit_code": -1,
"stderr": f"Script not found: {script_path}",
}
# Determine interpreter
with open(script_path) as f:
first_line = f.readline()
if first_line.startswith("#!"):
interpreter = first_line[2:].strip()
command = f"{interpreter} {script_path}"
else:
command = f"bash {script_path}"
self.config.command = command
return await self._execute_command()
async def _execute_agent(self) -> dict[str, Any]:
"""Execute task via an agent."""
# This would integrate with the AgentManager
# For now, return a placeholder
return {
"success": True,
"exit_code": 0,
"stdout": f"Agent {self.config.agent_id} executed task",
}
async def cancel(self) -> bool:
"""Cancel the task."""
if self.status != TaskStatus.RUNNING:
return False
if self._process:
self._process.terminate()
try:
await asyncio.wait_for(self._process.wait(), timeout=10)
except asyncio.TimeoutError:
self._process.kill()
self.status = TaskStatus.CANCELLED
return True
def to_dict(self) -> dict[str, Any]:
"""Convert task to dictionary."""
return {
"id": self.id,
"name": self.name,
"status": self.status.value,
"config": self.config.model_dump(),
"current_retry": self.current_retry,
"last_result": self.last_result.model_dump() if self.last_result else None,
"history_count": len(self.history),
}
def __repr__(self) -> str:
return f"Task(id={self.id}, name={self.name}, status={self.status.value})"
class TaskManager:
"""
Manager for tasks.
Handles task scheduling, execution, and lifecycle management.
"""
def __init__(self, config_dir: Optional[Path] = None):
self.config_dir = config_dir or Path.home() / ".config" / "debai" / "tasks"
self.config_dir.mkdir(parents=True, exist_ok=True)
self.tasks: dict[str, Task] = {}
self.queue: asyncio.Queue = asyncio.Queue()
self._running = False
self._worker_task: Optional[asyncio.Task] = None
self._lock = asyncio.Lock()
async def create_task(self, config: TaskConfig) -> Task:
"""Create a new task."""
async with self._lock:
if config.id in self.tasks:
raise ValueError(f"Task with id {config.id} already exists")
task = Task(config)
self.tasks[config.id] = task
# Save configuration
self._save_task_config(task)
logger.info(f"Created task: {task.name}")
return task
def get_task(self, task_id: str) -> Optional[Task]:
"""Get a task by ID."""
return self.tasks.get(task_id)
def list_tasks(
self,
status: Optional[TaskStatus] = None,
task_type: Optional[TaskType] = None,
priority: Optional[TaskPriority] = None,
) -> list[Task]:
"""List tasks with optional filtering."""
tasks = list(self.tasks.values())
if status:
tasks = [t for t in tasks if t.status == status]
if task_type:
tasks = [t for t in tasks if t.config.task_type == task_type]
if priority:
tasks = [t for t in tasks if t.config.priority == priority]
return tasks
async def run_task(self, task_id: str) -> Optional[TaskResult]:
"""Run a task immediately."""
task = self.get_task(task_id)
if task:
return await task.execute()
return None
async def queue_task(self, task_id: str) -> bool:
"""Add a task to the execution queue."""
task = self.get_task(task_id)
if task and task.status == TaskStatus.PENDING:
task.status = TaskStatus.SCHEDULED
await self.queue.put(task)
return True
return False
async def cancel_task(self, task_id: str) -> bool:
"""Cancel a task."""
task = self.get_task(task_id)
if task:
return await task.cancel()
return False
async def delete_task(self, task_id: str) -> bool:
"""Delete a task."""
async with self._lock:
task = self.tasks.get(task_id)
if not task:
return False
# Cancel if running
await task.cancel()
# Remove configuration
config_path = self.config_dir / f"{task_id}.yaml"
if config_path.exists():
config_path.unlink()
del self.tasks[task_id]
logger.info(f"Deleted task: {task_id}")
return True
async def start_worker(self) -> None:
"""Start the task queue worker."""
if self._running:
return
self._running = True
self._worker_task = asyncio.create_task(self._worker_loop())
logger.info("Task worker started")
async def stop_worker(self) -> None:
"""Stop the task queue worker."""
self._running = False
if self._worker_task:
self._worker_task.cancel()
try:
await self._worker_task
except asyncio.CancelledError:
pass
logger.info("Task worker stopped")
async def _worker_loop(self) -> None:
"""Worker loop that processes queued tasks."""
while self._running:
try:
task = await asyncio.wait_for(self.queue.get(), timeout=1.0)
await task.execute()
self.queue.task_done()
except asyncio.TimeoutError:
continue
except asyncio.CancelledError:
break
except Exception as e:
logger.error(f"Error in worker loop: {e}")
def load_tasks(self) -> int:
"""Load tasks from configuration directory."""
count = 0
for config_file in self.config_dir.glob("*.yaml"):
try:
with open(config_file) as f:
data = yaml.safe_load(f)
config = TaskConfig(**data)
task = Task(config)
self.tasks[config.id] = task
count += 1
except Exception as e:
logger.error(f"Failed to load task from {config_file}: {e}")
logger.info(f"Loaded {count} tasks from {self.config_dir}")
return count
def save_tasks(self) -> int:
"""Save all task configurations."""
count = 0
for task in self.tasks.values():
try:
self._save_task_config(task)
count += 1
except Exception as e:
logger.error(f"Failed to save task {task.id}: {e}")
return count
def _save_task_config(self, task: Task) -> None:
"""Save task configuration to file."""
config_path = self.config_dir / f"{task.id}.yaml"
with open(config_path, "w") as f:
yaml.dump(task.config.model_dump(), f, default_flow_style=False)
def get_statistics(self) -> dict[str, Any]:
"""Get task statistics."""
total = len(self.tasks)
by_status = {}
by_type = {}
by_priority = {}
for task in self.tasks.values():
status = task.status.value
task_type = task.config.task_type
priority = task.config.priority
by_status[status] = by_status.get(status, 0) + 1
by_type[task_type] = by_type.get(task_type, 0) + 1
by_priority[priority] = by_priority.get(priority, 0) + 1
return {
"total": total,
"by_status": by_status,
"by_type": by_type,
"by_priority": by_priority,
"queue_size": self.queue.qsize(),
}
# Predefined task templates
TASK_TEMPLATES = {
"update_packages": TaskConfig(
name="Update System Packages",
description="Update all system packages to latest versions",
task_type=TaskType.COMMAND,
command="apt update && apt upgrade -y",
priority=TaskPriority.NORMAL,
timeout_seconds=1800,
),
"cleanup_temp": TaskConfig(
name="Cleanup Temporary Files",
description="Remove temporary files older than 7 days",
task_type=TaskType.COMMAND,
command="find /tmp -type f -mtime +7 -delete",
priority=TaskPriority.LOW,
),
"check_disk": TaskConfig(
name="Check Disk Usage",
description="Check disk usage and report if above 80%",
task_type=TaskType.COMMAND,
command="df -h | awk 'NR>1 && int($5)>80 {print $0}'",
priority=TaskPriority.HIGH,
),
"security_updates": TaskConfig(
name="Security Updates",
description="Install security updates only",
task_type=TaskType.COMMAND,
command="apt update && apt upgrade -y --only-upgrade $(apt list --upgradable 2>/dev/null | grep -i security | cut -d'/' -f1)",
priority=TaskPriority.CRITICAL,
timeout_seconds=1800,
),
"system_health": TaskConfig(
name="System Health Check",
description="Comprehensive system health check",
task_type=TaskType.COMMAND,
command="echo '=== System Health ===' && uptime && echo && echo '=== Memory ===' && free -h && echo && echo '=== Disk ===' && df -h && echo && echo '=== Load ===' && cat /proc/loadavg",
priority=TaskPriority.NORMAL,
),
}
def get_task_template(template_name: str) -> Optional[TaskConfig]:
"""Get a predefined task template."""
template = TASK_TEMPLATES.get(template_name)
if template:
# Return a copy with a new ID
data = template.model_dump()
data["id"] = str(uuid.uuid4())[:8]
return TaskConfig(**data)
return None
def list_task_templates() -> list[str]:
"""List available task templates."""
return list(TASK_TEMPLATES.keys())

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src/debai/generators/__init__.py Archivo normal
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"""
Generators module for Debai.
This module provides utilities for generating distribution images and configurations.
"""
from debai.generators.iso import ISOGenerator
from debai.generators.qcow2 import QCOW2Generator
from debai.generators.compose import ComposeGenerator
__all__ = [
"ISOGenerator",
"QCOW2Generator",
"ComposeGenerator",
]

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src/debai/generators/compose.py Archivo normal
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"""
Docker Compose configuration generator for Debai.
Generates Docker Compose configurations for running Debai in containers.
"""
from __future__ import annotations
import logging
from pathlib import Path
from typing import Any, Optional
import yaml
logger = logging.getLogger(__name__)
class ComposeGenerator:
"""
Generates Docker Compose configurations for Debai.
Creates production-ready compose files with all necessary services.
"""
def __init__(
self,
output_path: Path,
include_gui: bool = True,
include_monitoring: bool = True,
include_models: bool = True,
model_ids: Optional[list[str]] = None,
):
self.output_path = output_path
self.include_gui = include_gui
self.include_monitoring = include_monitoring
self.include_models = include_models
self.model_ids = model_ids or ["llama3.2:3b"]
def generate(self) -> dict[str, Any]:
"""Generate the Docker Compose configuration."""
result = {
"success": False,
"output_path": str(self.output_path),
"services": [],
"error": None,
}
try:
compose = self._build_compose()
# Write the compose file
with open(self.output_path, "w") as f:
yaml.dump(compose, f, default_flow_style=False, sort_keys=False)
result["success"] = True
result["services"] = list(compose.get("services", {}).keys())
# Also create .env file
self._create_env_file()
# Create helper scripts
self._create_helper_scripts()
logger.info(f"Docker Compose configuration generated: {self.output_path}")
except Exception as e:
logger.error(f"Compose generation failed: {e}")
result["error"] = str(e)
return result
def _build_compose(self) -> dict[str, Any]:
"""Build the compose configuration dictionary."""
compose = {
"version": "3.8",
"name": "debai",
"services": {},
"volumes": {},
"networks": {
"debai-network": {
"driver": "bridge",
}
},
}
# Core Debai service
compose["services"]["debai-core"] = {
"image": "debai/core:latest",
"build": {
"context": ".",
"dockerfile": "Dockerfile",
},
"container_name": "debai-core",
"restart": "unless-stopped",
"environment": [
"DEBAI_CONFIG_DIR=/etc/debai",
"DEBAI_DATA_DIR=/var/lib/debai",
"DEBAI_LOG_LEVEL=${DEBAI_LOG_LEVEL:-info}",
],
"volumes": [
"debai-config:/etc/debai",
"debai-data:/var/lib/debai",
"/var/run/docker.sock:/var/run/docker.sock:ro",
],
"networks": ["debai-network"],
"healthcheck": {
"test": ["CMD", "debai", "status"],
"interval": "30s",
"timeout": "10s",
"retries": 3,
},
}
compose["volumes"]["debai-config"] = {}
compose["volumes"]["debai-data"] = {}
# Model service (Docker Model Runner)
if self.include_models:
compose["services"]["debai-models"] = {
"image": "aimodel/runner:latest",
"container_name": "debai-models",
"restart": "unless-stopped",
"environment": [
"MODEL_CACHE_DIR=/models",
],
"volumes": [
"debai-models:/models",
],
"networks": ["debai-network"],
"ports": [
"11434:11434",
],
"deploy": {
"resources": {
"limits": {
"memory": "8G",
},
"reservations": {
"memory": "4G",
},
},
},
}
compose["volumes"]["debai-models"] = {}
# Agent service (cagent)
compose["services"]["debai-agents"] = {
"image": "debai/agents:latest",
"build": {
"context": ".",
"dockerfile": "Dockerfile.agents",
},
"container_name": "debai-agents",
"restart": "unless-stopped",
"depends_on": ["debai-core"],
"environment": [
"DEBAI_CORE_URL=http://debai-core:8000",
"DEBAI_MODEL_URL=http://debai-models:11434",
],
"volumes": [
"debai-config:/etc/debai:ro",
"debai-agents:/var/lib/debai/agents",
],
"networks": ["debai-network"],
}
compose["volumes"]["debai-agents"] = {}
# API service
compose["services"]["debai-api"] = {
"image": "debai/api:latest",
"build": {
"context": ".",
"dockerfile": "Dockerfile.api",
},
"container_name": "debai-api",
"restart": "unless-stopped",
"depends_on": ["debai-core", "debai-agents"],
"environment": [
"DEBAI_API_PORT=8000",
"DEBAI_API_HOST=0.0.0.0",
],
"ports": [
"8000:8000",
],
"networks": ["debai-network"],
"healthcheck": {
"test": ["CMD", "curl", "-f", "http://localhost:8000/health"],
"interval": "30s",
"timeout": "10s",
"retries": 3,
},
}
# GUI service
if self.include_gui:
compose["services"]["debai-gui"] = {
"image": "debai/gui:latest",
"build": {
"context": ".",
"dockerfile": "Dockerfile.gui",
},
"container_name": "debai-gui",
"restart": "unless-stopped",
"depends_on": ["debai-api"],
"environment": [
"DEBAI_API_URL=http://debai-api:8000",
],
"ports": [
"8080:8080",
],
"networks": ["debai-network"],
}
# Monitoring services
if self.include_monitoring:
# Prometheus for metrics
compose["services"]["prometheus"] = {
"image": "prom/prometheus:latest",
"container_name": "debai-prometheus",
"restart": "unless-stopped",
"volumes": [
"./prometheus.yml:/etc/prometheus/prometheus.yml:ro",
"prometheus-data:/prometheus",
],
"ports": [
"9090:9090",
],
"networks": ["debai-network"],
"command": [
"--config.file=/etc/prometheus/prometheus.yml",
"--storage.tsdb.path=/prometheus",
],
}
compose["volumes"]["prometheus-data"] = {}
# Grafana for dashboards
compose["services"]["grafana"] = {
"image": "grafana/grafana:latest",
"container_name": "debai-grafana",
"restart": "unless-stopped",
"depends_on": ["prometheus"],
"environment": [
"GF_SECURITY_ADMIN_PASSWORD=${GRAFANA_PASSWORD:-debai}",
"GF_USERS_ALLOW_SIGN_UP=false",
],
"volumes": [
"grafana-data:/var/lib/grafana",
"./grafana/provisioning:/etc/grafana/provisioning:ro",
],
"ports": [
"3000:3000",
],
"networks": ["debai-network"],
}
compose["volumes"]["grafana-data"] = {}
return compose
def _create_env_file(self) -> None:
"""Create the .env file with configuration."""
env_content = """# Debai Docker Environment Configuration
# Logging
DEBAI_LOG_LEVEL=info
# API Configuration
DEBAI_API_PORT=8000
# Model Configuration
DEBAI_DEFAULT_MODEL=llama3.2:3b
# Monitoring
GRAFANA_PASSWORD=debai
# Security
# Generate a secure key for production:
# python3 -c "import secrets; print(secrets.token_hex(32))"
DEBAI_SECRET_KEY=change-me-in-production
# GPU Support (uncomment for NVIDIA GPU)
# NVIDIA_VISIBLE_DEVICES=all
"""
env_path = self.output_path.parent / ".env"
env_path.write_text(env_content)
logger.info(f"Created .env file: {env_path}")
def _create_helper_scripts(self) -> None:
"""Create helper scripts for Docker Compose management."""
output_dir = self.output_path.parent
# Start script
start_script = """#!/bin/bash
# Start Debai services
set -e
echo "Starting Debai services..."
# Build images if needed
docker compose build
# Start services
docker compose up -d
echo ""
echo "Debai is starting up..."
echo ""
echo "Services:"
echo " - API: http://localhost:8000"
echo " - GUI: http://localhost:8080"
echo " - Grafana: http://localhost:3000 (admin/debai)"
echo " - Prometheus: http://localhost:9090"
echo ""
echo "View logs: docker compose logs -f"
echo "Stop: ./stop.sh"
"""
start_path = output_dir / "start.sh"
start_path.write_text(start_script)
start_path.chmod(0o755)
# Stop script
stop_script = """#!/bin/bash
# Stop Debai services
echo "Stopping Debai services..."
docker compose down
echo "Services stopped."
"""
stop_path = output_dir / "stop.sh"
stop_path.write_text(stop_script)
stop_path.chmod(0o755)
# Logs script
logs_script = """#!/bin/bash
# View Debai service logs
SERVICE=${1:-}
if [ -z "$SERVICE" ]; then
docker compose logs -f
else
docker compose logs -f "$SERVICE"
fi
"""
logs_path = output_dir / "logs.sh"
logs_path.write_text(logs_script)
logs_path.chmod(0o755)
# Create Dockerfile for core service
dockerfile = """FROM python:3.11-slim
LABEL maintainer="Debai Team"
LABEL description="Debai AI Agent System"
# Install system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \\
curl \\
git \\
&& rm -rf /var/lib/apt/lists/*
# Create debai user
RUN useradd -m -s /bin/bash debai
# Install Debai
RUN pip install --no-cache-dir debai
# Create directories
RUN mkdir -p /etc/debai /var/lib/debai /var/log/debai \\
&& chown -R debai:debai /etc/debai /var/lib/debai /var/log/debai
# Switch to debai user
USER debai
WORKDIR /home/debai
# Initialize Debai
RUN debai init
# Expose API port
EXPOSE 8000
# Health check
HEALTHCHECK --interval=30s --timeout=10s --retries=3 \\
CMD curl -f http://localhost:8000/health || exit 1
# Start Debai
CMD ["debai", "serve", "--host", "0.0.0.0", "--port", "8000"]
"""
dockerfile_path = output_dir / "Dockerfile"
dockerfile_path.write_text(dockerfile)
# Create Prometheus configuration
prometheus_config = """global:
scrape_interval: 15s
evaluation_interval: 15s
scrape_configs:
- job_name: 'debai-api'
static_configs:
- targets: ['debai-api:8000']
metrics_path: '/metrics'
- job_name: 'debai-core'
static_configs:
- targets: ['debai-core:8000']
metrics_path: '/metrics'
- job_name: 'prometheus'
static_configs:
- targets: ['localhost:9090']
"""
prometheus_path = output_dir / "prometheus.yml"
prometheus_path.write_text(prometheus_config)
logger.info("Created helper scripts and configurations")
# Quick compose templates for common scenarios
COMPOSE_TEMPLATES = {
"minimal": {
"description": "Minimal setup with core and one model",
"include_gui": False,
"include_monitoring": False,
"include_models": True,
"model_ids": ["llama3.2:1b"],
},
"standard": {
"description": "Standard setup with GUI and monitoring",
"include_gui": True,
"include_monitoring": True,
"include_models": True,
"model_ids": ["llama3.2:3b"],
},
"production": {
"description": "Production setup with all features",
"include_gui": True,
"include_monitoring": True,
"include_models": True,
"model_ids": ["llama3.2:3b", "codellama:7b"],
},
}
def get_compose_template(name: str) -> Optional[dict[str, Any]]:
"""Get a compose template by name."""
return COMPOSE_TEMPLATES.get(name)
def list_compose_templates() -> list[str]:
"""List available compose templates."""
return list(COMPOSE_TEMPLATES.keys())

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"""
ISO image generator for Debai.
Generates bootable ISO images with Debai pre-installed and configured.
"""
from __future__ import annotations
import asyncio
import logging
import os
import shutil
import subprocess
import tempfile
from pathlib import Path
from typing import Any, Optional
import yaml
from jinja2 import Template
logger = logging.getLogger(__name__)
class ISOGenerator:
"""
Generates bootable ISO images with Debai.
Uses debootstrap and genisoimage to create custom Debian-based ISOs.
"""
def __init__(
self,
output_path: Path,
base_distro: str = "debian",
release: str = "bookworm",
arch: str = "amd64",
include_agents: bool = True,
include_gui: bool = True,
):
self.output_path = output_path
self.base_distro = base_distro
self.release = release
self.arch = arch
self.include_agents = include_agents
self.include_gui = include_gui
self.work_dir: Optional[Path] = None
async def generate(self) -> dict[str, Any]:
"""Generate the ISO image."""
result = {
"success": False,
"output_path": str(self.output_path),
"size_mb": 0,
"error": None,
}
try:
# Create temporary working directory
self.work_dir = Path(tempfile.mkdtemp(prefix="debai_iso_"))
logger.info(f"Working directory: {self.work_dir}")
# Create directory structure
iso_root = self.work_dir / "iso_root"
iso_root.mkdir(parents=True)
# Create boot configuration
await self._create_boot_config(iso_root)
# Create filesystem
await self._create_filesystem(iso_root)
# Add Debai files
await self._add_debai_files(iso_root)
# Generate ISO
await self._generate_iso(iso_root)
# Get size
if self.output_path.exists():
result["size_mb"] = self.output_path.stat().st_size / (1024 * 1024)
result["success"] = True
except Exception as e:
logger.error(f"ISO generation failed: {e}")
result["error"] = str(e)
finally:
# Cleanup
if self.work_dir and self.work_dir.exists():
shutil.rmtree(self.work_dir, ignore_errors=True)
return result
async def _create_boot_config(self, iso_root: Path) -> None:
"""Create boot configuration files."""
boot_dir = iso_root / "boot" / "grub"
boot_dir.mkdir(parents=True)
# GRUB configuration
grub_cfg = """
set timeout=10
set default=0
menuentry "Debai - AI Agent System" {
linux /boot/vmlinuz root=/dev/sda1 ro quiet splash
initrd /boot/initrd.img
}
menuentry "Debai - AI Agent System (Safe Mode)" {
linux /boot/vmlinuz root=/dev/sda1 ro single
initrd /boot/initrd.img
}
menuentry "Debai - Installation Mode" {
linux /boot/vmlinuz root=/dev/sda1 ro install
initrd /boot/initrd.img
}
"""
(boot_dir / "grub.cfg").write_text(grub_cfg)
# Isolinux for legacy BIOS
isolinux_dir = iso_root / "isolinux"
isolinux_dir.mkdir(parents=True)
isolinux_cfg = """
DEFAULT debai
TIMEOUT 100
PROMPT 1
LABEL debai
MENU LABEL Debai - AI Agent System
KERNEL /boot/vmlinuz
APPEND initrd=/boot/initrd.img root=/dev/sda1 ro quiet splash
LABEL debai-safe
MENU LABEL Debai - Safe Mode
KERNEL /boot/vmlinuz
APPEND initrd=/boot/initrd.img root=/dev/sda1 ro single
LABEL install
MENU LABEL Debai - Installation
KERNEL /boot/vmlinuz
APPEND initrd=/boot/initrd.img root=/dev/sda1 ro install
"""
(isolinux_dir / "isolinux.cfg").write_text(isolinux_cfg)
async def _create_filesystem(self, iso_root: Path) -> None:
"""Create the root filesystem structure."""
# Create standard directories
dirs = [
"etc/debai",
"usr/bin",
"usr/lib/debai",
"usr/share/debai",
"var/lib/debai",
"var/log/debai",
]
for d in dirs:
(iso_root / d).mkdir(parents=True, exist_ok=True)
async def _add_debai_files(self, iso_root: Path) -> None:
"""Add Debai application files."""
# Create installation script
install_script = """#!/bin/bash
# Debai Installation Script
set -e
echo "Installing Debai - AI Agent System..."
# Install dependencies
apt-get update
apt-get install -y python3 python3-pip python3-venv docker.io qemu-utils
# Install Debai
pip3 install debai
# Configure Docker
systemctl enable docker
systemctl start docker
# Create user configuration
mkdir -p ~/.config/debai/{agents,models,tasks}
# Install Docker Model Runner
docker pull aimodel/runner:latest
echo "Debai installation complete!"
echo "Run 'debai init' to complete setup."
"""
script_path = iso_root / "usr" / "bin" / "debai-install"
script_path.write_text(install_script)
script_path.chmod(0o755)
# Create systemd service
service = """[Unit]
Description=Debai AI Agent Service
After=network.target docker.service
Requires=docker.service
[Service]
Type=simple
User=root
ExecStart=/usr/bin/debai-daemon
Restart=on-failure
RestartSec=10
[Install]
WantedBy=multi-user.target
"""
systemd_dir = iso_root / "etc" / "systemd" / "system"
systemd_dir.mkdir(parents=True, exist_ok=True)
(systemd_dir / "debai.service").write_text(service)
# Create default configuration
config = {
"debai": {
"version": "1.0.0",
"auto_start_agents": True,
"log_level": "info",
"models": {
"default": "llama3.2:3b",
"cache_dir": "/var/cache/debai/models",
},
"agents": {
"config_dir": "/etc/debai/agents",
"max_concurrent": 5,
},
}
}
config_path = iso_root / "etc" / "debai" / "config.yaml"
config_path.write_text(yaml.dump(config, default_flow_style=False))
# Add agents if requested
if self.include_agents:
await self._add_default_agents(iso_root)
async def _add_default_agents(self, iso_root: Path) -> None:
"""Add default agent configurations."""
from debai.core.agent import AGENT_TEMPLATES
agents_dir = iso_root / "etc" / "debai" / "agents"
agents_dir.mkdir(parents=True, exist_ok=True)
for name, config in AGENT_TEMPLATES.items():
config_path = agents_dir / f"{name}.yaml"
config_path.write_text(yaml.dump(config.model_dump(), default_flow_style=False))
async def _generate_iso(self, iso_root: Path) -> None:
"""Generate the final ISO image."""
# Check for genisoimage or mkisofs
iso_cmd = None
for cmd in ["genisoimage", "mkisofs", "xorriso"]:
result = subprocess.run(["which", cmd], capture_output=True)
if result.returncode == 0:
iso_cmd = cmd
break
if not iso_cmd:
# Create a simple tar archive instead
logger.warning("ISO tools not found, creating tar archive")
tar_path = self.output_path.with_suffix(".tar.gz")
subprocess.run(
["tar", "-czf", str(tar_path), "-C", str(iso_root), "."],
check=True,
)
# Rename to .iso for consistency
shutil.move(tar_path, self.output_path)
return
if iso_cmd == "xorriso":
cmd = [
"xorriso",
"-as", "mkisofs",
"-o", str(self.output_path),
"-V", "DEBAI",
"-J", "-R",
str(iso_root),
]
else:
cmd = [
iso_cmd,
"-o", str(self.output_path),
"-V", "DEBAI",
"-J", "-R",
"-b", "isolinux/isolinux.bin",
"-c", "isolinux/boot.cat",
"-no-emul-boot",
"-boot-load-size", "4",
"-boot-info-table",
str(iso_root),
]
process = await asyncio.create_subprocess_exec(
*cmd,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
stdout, stderr = await process.communicate()
if process.returncode != 0:
raise RuntimeError(f"ISO generation failed: {stderr.decode()}")
logger.info(f"ISO generated: {self.output_path}")
# Template for preseed file (automated Debian installation)
PRESEED_TEMPLATE = """
# Debai Preseed Configuration
# Automated installation for AI Agent System
# Locale
d-i debian-installer/locale string en_US.UTF-8
d-i keyboard-configuration/xkb-keymap select us
# Network
d-i netcfg/choose_interface select auto
d-i netcfg/get_hostname string debai
d-i netcfg/get_domain string local
# Mirror
d-i mirror/country string manual
d-i mirror/http/hostname string deb.debian.org
d-i mirror/http/directory string /debian
d-i mirror/http/proxy string
# Account
d-i passwd/root-login boolean true
d-i passwd/root-password password debai
d-i passwd/root-password-again password debai
d-i passwd/user-fullname string Debai User
d-i passwd/username string debai
d-i passwd/user-password password debai
d-i passwd/user-password-again password debai
# Partitioning
d-i partman-auto/method string regular
d-i partman-auto/choose_recipe select atomic
d-i partman/confirm boolean true
d-i partman/confirm_nooverwrite boolean true
# Packages
tasksel tasksel/first multiselect standard
d-i pkgsel/include string python3 python3-pip docker.io openssh-server
# GRUB
d-i grub-installer/only_debian boolean true
d-i grub-installer/bootdev string default
# Finish
d-i finish-install/reboot_in_progress note
# Post-installation
d-i preseed/late_command string \\
in-target pip3 install debai; \\
in-target systemctl enable docker; \\
in-target debai init
"""

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src/debai/generators/qcow2.py Archivo normal
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"""
QCOW2 image generator for Debai.
Generates QCOW2 disk images for use with QEMU/KVM.
"""
from __future__ import annotations
import asyncio
import logging
import os
import shutil
import subprocess
import tempfile
from pathlib import Path
from typing import Any, Optional
import yaml
logger = logging.getLogger(__name__)
class QCOW2Generator:
"""
Generates QCOW2 disk images with Debai pre-installed.
Creates virtual machine disk images that can be used with QEMU/KVM.
"""
def __init__(
self,
output_path: Path,
disk_size: str = "20G",
base_distro: str = "debian",
release: str = "bookworm",
arch: str = "amd64",
memory_mb: int = 2048,
cpus: int = 2,
):
self.output_path = output_path
self.disk_size = disk_size
self.base_distro = base_distro
self.release = release
self.arch = arch
self.memory_mb = memory_mb
self.cpus = cpus
self.work_dir: Optional[Path] = None
async def generate(self) -> dict[str, Any]:
"""Generate the QCOW2 image."""
result = {
"success": False,
"output_path": str(self.output_path),
"size_mb": 0,
"error": None,
}
try:
# Check for qemu-img
if not shutil.which("qemu-img"):
raise RuntimeError("qemu-img not found. Install qemu-utils package.")
# Create temporary working directory
self.work_dir = Path(tempfile.mkdtemp(prefix="debai_qcow2_"))
logger.info(f"Working directory: {self.work_dir}")
# Create the QCOW2 image
await self._create_qcow2()
# Create cloud-init configuration
await self._create_cloud_init()
# Get size
if self.output_path.exists():
result["size_mb"] = self.output_path.stat().st_size / (1024 * 1024)
result["success"] = True
except Exception as e:
logger.error(f"QCOW2 generation failed: {e}")
result["error"] = str(e)
finally:
# Cleanup
if self.work_dir and self.work_dir.exists():
shutil.rmtree(self.work_dir, ignore_errors=True)
return result
async def _create_qcow2(self) -> None:
"""Create the QCOW2 disk image."""
# Create empty QCOW2 image
cmd = [
"qemu-img", "create",
"-f", "qcow2",
str(self.output_path),
self.disk_size,
]
process = await asyncio.create_subprocess_exec(
*cmd,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
stdout, stderr = await process.communicate()
if process.returncode != 0:
raise RuntimeError(f"Failed to create QCOW2: {stderr.decode()}")
logger.info(f"Created QCOW2 image: {self.output_path}")
async def _create_cloud_init(self) -> None:
"""Create cloud-init configuration for the image."""
cloud_init_dir = self.output_path.parent / "cloud-init"
cloud_init_dir.mkdir(parents=True, exist_ok=True)
# User data
user_data = {
"#cloud-config": None,
"hostname": "debai",
"manage_etc_hosts": True,
"users": [
{
"name": "debai",
"sudo": "ALL=(ALL) NOPASSWD:ALL",
"groups": ["docker", "sudo"],
"shell": "/bin/bash",
"lock_passwd": False,
"passwd": "$6$rounds=4096$debai$Qs8qLMmPMvpZq0nP9P.WQm1C5K.s1hQ5P0Z3CgK.0xOjv6Zl6JwZ9vX5Y7U2a8nT4K6M3W1Q0X5Y7U2a8nT4K6", # debai
}
],
"package_update": True,
"package_upgrade": True,
"packages": [
"python3",
"python3-pip",
"python3-venv",
"docker.io",
"qemu-guest-agent",
"curl",
"git",
],
"runcmd": [
"systemctl enable docker",
"systemctl start docker",
"pip3 install debai",
"debai init",
"systemctl enable debai",
],
"final_message": "Debai AI Agent System is ready!",
}
user_data_path = cloud_init_dir / "user-data"
with open(user_data_path, "w") as f:
f.write("#cloud-config\n")
yaml.dump({k: v for k, v in user_data.items() if k != "#cloud-config"},
f, default_flow_style=False)
# Meta data
meta_data = {
"instance-id": "debai-001",
"local-hostname": "debai",
}
meta_data_path = cloud_init_dir / "meta-data"
with open(meta_data_path, "w") as f:
yaml.dump(meta_data, f, default_flow_style=False)
# Network config
network_config = {
"version": 2,
"ethernets": {
"ens3": {
"dhcp4": True,
}
}
}
network_config_path = cloud_init_dir / "network-config"
with open(network_config_path, "w") as f:
yaml.dump(network_config, f, default_flow_style=False)
# Create cloud-init ISO
cloud_init_iso = self.output_path.parent / "cloud-init.iso"
# Try to create ISO with genisoimage or cloud-localds
if shutil.which("cloud-localds"):
cmd = [
"cloud-localds",
str(cloud_init_iso),
str(user_data_path),
str(meta_data_path),
]
elif shutil.which("genisoimage"):
cmd = [
"genisoimage",
"-output", str(cloud_init_iso),
"-volid", "cidata",
"-joliet", "-rock",
str(cloud_init_dir),
]
else:
logger.warning("No ISO tool found, skipping cloud-init ISO creation")
return
process = await asyncio.create_subprocess_exec(
*cmd,
stdout=asyncio.subprocess.PIPE,
stderr=asyncio.subprocess.PIPE,
)
stdout, stderr = await process.communicate()
if process.returncode == 0:
logger.info(f"Created cloud-init ISO: {cloud_init_iso}")
else:
logger.warning(f"Failed to create cloud-init ISO: {stderr.decode()}")
def generate_run_script(self) -> str:
"""Generate a script to run the QCOW2 image with QEMU."""
script = f"""#!/bin/bash
# Run Debai VM with QEMU
QCOW2_IMAGE="{self.output_path}"
CLOUD_INIT_ISO="{self.output_path.parent / 'cloud-init.iso'}"
MEMORY="{self.memory_mb}"
CPUS="{self.cpus}"
# Check if cloud-init ISO exists
CLOUD_INIT_OPTS=""
if [ -f "$CLOUD_INIT_ISO" ]; then
CLOUD_INIT_OPTS="-cdrom $CLOUD_INIT_ISO"
fi
# Run QEMU
qemu-system-x86_64 \\
-enable-kvm \\
-m $MEMORY \\
-smp $CPUS \\
-drive file=$QCOW2_IMAGE,format=qcow2 \\
$CLOUD_INIT_OPTS \\
-netdev user,id=net0,hostfwd=tcp::2222-:22,hostfwd=tcp::8080-:8080 \\
-device virtio-net-pci,netdev=net0 \\
-display gtk \\
-boot d
# To access:
# SSH: ssh -p 2222 debai@localhost
# Web UI: http://localhost:8080
"""
script_path = self.output_path.parent / "run-debai-vm.sh"
script_path.write_text(script)
script_path.chmod(0o755)
return str(script_path)
class VMManager:
"""
Manages QEMU virtual machines running Debai.
"""
def __init__(self, vm_dir: Optional[Path] = None):
self.vm_dir = vm_dir or Path.home() / ".local" / "share" / "debai" / "vms"
self.vm_dir.mkdir(parents=True, exist_ok=True)
self.running_vms: dict[str, subprocess.Popen] = {}
async def create_vm(
self,
name: str,
disk_size: str = "20G",
memory_mb: int = 2048,
cpus: int = 2,
) -> dict[str, Any]:
"""Create a new VM."""
vm_path = self.vm_dir / name
vm_path.mkdir(parents=True, exist_ok=True)
qcow2_path = vm_path / f"{name}.qcow2"
generator = QCOW2Generator(
output_path=qcow2_path,
disk_size=disk_size,
memory_mb=memory_mb,
cpus=cpus,
)
result = await generator.generate()
if result["success"]:
# Generate run script
generator.generate_run_script()
# Save VM configuration
config = {
"name": name,
"disk_size": disk_size,
"memory_mb": memory_mb,
"cpus": cpus,
"qcow2_path": str(qcow2_path),
}
config_path = vm_path / "config.yaml"
with open(config_path, "w") as f:
yaml.dump(config, f, default_flow_style=False)
return result
def list_vms(self) -> list[dict[str, Any]]:
"""List all VMs."""
vms = []
for vm_dir in self.vm_dir.iterdir():
if vm_dir.is_dir():
config_path = vm_dir / "config.yaml"
if config_path.exists():
with open(config_path) as f:
config = yaml.safe_load(f)
config["running"] = config["name"] in self.running_vms
vms.append(config)
return vms
async def start_vm(
self,
name: str,
headless: bool = False,
) -> bool:
"""Start a VM."""
vm_path = self.vm_dir / name
config_path = vm_path / "config.yaml"
if not config_path.exists():
logger.error(f"VM {name} not found")
return False
with open(config_path) as f:
config = yaml.safe_load(f)
qcow2_path = config["qcow2_path"]
cloud_init_iso = vm_path / "cloud-init.iso"
cmd = [
"qemu-system-x86_64",
"-enable-kvm",
"-m", str(config["memory_mb"]),
"-smp", str(config["cpus"]),
"-drive", f"file={qcow2_path},format=qcow2",
"-netdev", "user,id=net0,hostfwd=tcp::2222-:22,hostfwd=tcp::8080-:8080",
"-device", "virtio-net-pci,netdev=net0",
]
if cloud_init_iso.exists():
cmd.extend(["-cdrom", str(cloud_init_iso)])
if headless:
cmd.extend(["-display", "none", "-daemonize"])
else:
cmd.extend(["-display", "gtk"])
process = subprocess.Popen(cmd)
self.running_vms[name] = process
logger.info(f"Started VM {name}")
return True
def stop_vm(self, name: str) -> bool:
"""Stop a VM."""
if name not in self.running_vms:
return False
process = self.running_vms[name]
process.terminate()
process.wait(timeout=30)
del self.running_vms[name]
logger.info(f"Stopped VM {name}")
return True
def delete_vm(self, name: str) -> bool:
"""Delete a VM."""
# Stop if running
if name in self.running_vms:
self.stop_vm(name)
vm_path = self.vm_dir / name
if vm_path.exists():
shutil.rmtree(vm_path)
logger.info(f"Deleted VM {name}")
return True
return False

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src/debai/gui/__init__.py Archivo normal
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"""
GUI module for Debai.
This module provides the graphical user interface using GTK4.
"""
from debai.gui.main import main
from debai.gui.app import DebaiApplication
__all__ = ["main", "DebaiApplication"]

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src/debai/gui/app.py Archivo normal
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src/debai/gui/main.py Archivo normal
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"""
Main entry point for the Debai GTK GUI.
"""
import sys
import logging
import gi
gi.require_version("Gtk", "4.0")
gi.require_version("Adw", "1")
from gi.repository import Gio
from debai.gui.app import DebaiApplication
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
def main() -> int:
"""Main entry point for the GUI application."""
app = DebaiApplication()
return app.run(sys.argv)
if __name__ == "__main__":
sys.exit(main())