Metadata-Version: 2.4
Name: bosskit
Version: 0.0.1
Summary: BossNet AI Agent Toolkit - Python library for building AI-powered agents
Author-email: BossNet <info@boss-net.com>
Project-URL: Homepage, https://github.com/boss-net/ai-masterclass
Project-URL: Documentation, https://bosskit.readthedocs.io/
Project-URL: Issues, https://github.com/boss-net/ai-masterclass/issues
Keywords: ai,machine learning,agents,python
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries
Classifier: Operating System :: OS Independent
Requires-Python: <3.14,>=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file

# BossNet AI Agent Toolkit

[![Build Status](https://travis-ci.org/BossNet/bosskit.svg?branch=master)](https://travis-ci.org/BossNet/bosskit)
[![Documentation Status](https://readthedocs.org/projects/bosskit/badge/?version=latest)](https://bosskit.readthedocs.io/en/latest/?badge=latest)
[![PyPI version](https://badge.fury.io/py/bosskit.svg)](https://badge.fury.io/py/bosskit)

BossNet AI Agent Toolkit is a Python library for building AI-powered agents. It provides a comprehensive set of tools and utilities for building, training, and deploying AI agents. BossKit is designed to be modular and extensible, allowing users to easily add new features and functionality to their agents.

## Installation

### Prerequisites

- Python 3.11 or higher
- Git
- pip (Python package manager)

### Using pip

To install BossKit using pip:

```bash
pip install bosskit
```

### From Source

1. Clone the repository:
```bash
git clone https://github.com/boss-net/ai-masterclass.git
cd ai-masterclass
```

2. Create a virtual environment (recommended):
```bash
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate
```

3. Install dependencies:
```bash
pip install -r requirements.txt
```

4. Install in development mode:
```bash
pip install -e .
```

## Getting Started

### Basic Usage

To create a new AI agent project:

```bash
bosskit init my_agent
```

This will create a new project structure with:
- Basic configuration files
- Example agent implementation
- Testing setup

### Configuration

BossKit uses environment variables for configuration. Create a `.env` file based on the `.env.example` template:

```bash
cp .env.example .env
```

Edit the `.env` file to configure your agent's behavior:

- `AGENT_NAME`: Name of your AI agent
- `MODEL_PATH`: Path to your AI model
- `API_KEY`: API key for external services (if needed)

### Running Your Agent

To run your AI agent:

```bash
bosskit run
```

Or with specific configuration:

```bash
bosskit run --config path/to/config.yaml
```

## Features

- Modular agent architecture
- Built-in support for popular AI models
- Easy configuration management
- Built-in monitoring and logging
- Extensible plugin system
- Development tools and utilities

## Development

### Setting up Development Environment

1. Install development dependencies:

1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Set up development environment:
   ```bash
   # Install pre-commit hooks
   pip install pre-commit
   pre-commit install

   # Install development dependencies
   pip install -r requirements-dev.txt
   ```
4. Make your changes and ensure they follow our code style:
   - Use type hints for all public functions and classes
   - Follow PEP 8 style guidelines
   - Write clear docstrings using Google style
   - Keep lines under 88 characters
   - Use descriptive variable names
5. Run tests and checks:
   ```bash
   # Run all tests
   pytest

   # Run type checking
   mypy .

   # Run linting
   flake8 .
   ```
6. Commit your changes with a descriptive message
7. Push to the branch (`git push origin feature/amazing-feature`)
8. Open a Pull Request

### Code Style Guidelines

- Use type hints for all public interfaces
- Follow Google-style docstrings:
  ```python
  def function_name(param: type) -> return_type:
      """Brief description.

      Args:
          param: Description of the parameter

      Returns:
          Description of the return value
      """
  ```
- Use descriptive variable names
- Keep functions focused and single-purpose
- Use context managers for file operations
- Handle exceptions appropriately
- Write unit tests for new functionality

### Type Hints

All public functions and classes should have proper type hints. For example:

```python
from typing import List, Optional, Dict

def process_data(
    data: List[str],
    config: Optional[Dict[str, Any]] = None
) -> List[str]:
    """Process input data with optional configuration.

    Args:
        data: List of input strings to process
        config: Optional configuration dictionary

    Returns:
        Processed data as list of strings
    """
    pass
```

### Error Handling

- Use specific exceptions rather than bare except clauses
- Provide clear error messages
- Use context managers for resource cleanup
- Handle common error cases gracefully

### Testing

- Write unit tests for new functionality
- Use pytest fixtures for test setup
- Mock external dependencies
- Test error conditions
- Keep tests focused and isolated

### Documentation

- Update relevant documentation when making changes
- Keep README.md up-to-date
- Document new features and breaking changes
- Include usage examples where applicable

### Git Workflow

- Use feature branches for new development
- Keep commits focused and atomic
- Write descriptive commit messages
- Rebase before merging
- Use conventional commit messages:
  - feat: for new features
  - fix: for bug fixes
  - docs: for documentation changes
  - style: for formatting changes
  - refactor: for code refactoring
  - test: for adding missing tests
  - chore: for maintenance tasks

### Security

- Never commit sensitive information
- Use environment variables for configuration
- Handle API keys securely
- Follow security best practices
- Regularly update dependencies

## Contributing

We welcome contributions from the community! Please follow these guidelines:

1. Check for existing issues before creating new ones
2. Follow our code style and guidelines
3. Write tests for new features
4. Update documentation
5. Be respectful and professional in all communications

By contributing to this project, you agree to abide by our Code of Conduct.

## License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.

## Support

For support, please open an issue on the [GitHub Issues](https://github.com/boss-net/ai-masterclass/issues) page.

## Contributing

Contributions are welcome! Please read our [Contributing Guidelines](CONTRIBUTING.md) before submitting a pull request.

## Acknowledgments

- Thanks to all contributors who have helped make this project possible
- Special thanks to the open source community for their support and contributions

## Documentation

For more detailed documentation, visit our [ReadTheDocs page](https://bosskit.readthedocs.io/en/latest/)
