Contribution Guidelines

Project Overview
Getting Started
- Installation
- Project Structure
How to Contribute
- Reporting Issues
- Submitting Pull Requests
Coding Standards
Areas Needing Contributions
Community and Support
License

Project Overview

swarms is a library focused on making it simple to orchestrate agents to automate real-world activities. The goal is to automate the world economy with these swarms of agents.

We need your help to:

Write Tests: Ensure the reliability and correctness of the codebase.
Improve Documentation: Maintain clear and comprehensive documentation.
Add New Orchestration Methods: Add multi-agent orchestration methods
Removing Defunct Code: Removing bad code

Your contributions will help us push the boundaries of AI and make this library a valuable resource for the community.

Getting Started

Installation

You can install swarms using pip:

pip3 install swarms

Alternatively, you can clone the repository:

git clone https://github.com/kyegomez/swarms

Project Structure

swarms/: Contains all the source code for the library.
examples/: Includes example scripts and notebooks demonstrating how to use the library.
tests/: (To be created) Will contain unit tests for the library.
docs/: (To be maintained) Contains documentation files.

How to Contribute

Reporting Issues

If you find any bugs, inconsistencies, or have suggestions for enhancements, please open an issue on GitHub:

Search Existing Issues: Before opening a new issue, check if it has already been reported.
Open a New Issue: If it hasn't been reported, create a new issue and provide detailed information.
- Title: A concise summary of the issue.
- Description: Detailed description, steps to reproduce, expected behavior, and any relevant logs or screenshots.
Label Appropriately: Use labels to categorize the issue (e.g., bug, enhancement, documentation).

Submitting Pull Requests

We welcome pull requests (PRs) for bug fixes, improvements, and new features. Please follow these guidelines:

Fork the Repository: Create a personal fork of the repository on GitHub.
Clone Your Fork: Clone your forked repository to your local machine.
```
git clone https://github.com/kyegomez/swarms.git
```
Create a New Branch: Use a descriptive branch name.
```
git checkout -b feature/your-feature-name
```
Make Your Changes: Implement your code, ensuring it adheres to the coding standards.
Add Tests: Write tests to cover your changes.
Commit Your Changes: Write clear and concise commit messages.
```
git commit -am "Add feature X"
```

Push to Your Fork:

git push origin feature/your-feature-name

Create a Pull Request:
- Go to the original repository on GitHub.
- Click on "New Pull Request".
- Select your branch and create the PR.
- Provide a clear description of your changes and reference any related issues.
Respond to Feedback: Be prepared to make changes based on code reviews.

Note: It's recommended to create small and focused PRs for easier review and faster integration.

Coding Standards

To maintain code quality and consistency, please adhere to the following standards.

Type Annotations

Mandatory: All functions and methods must have type annotations.

Example:

def add_numbers(a: int, b: int) -> int:
    return a + b

Benefits:
- Improves code readability.
- Helps with static type checking tools.

Docstrings and Documentation

Docstrings: Every public class, function, and method must have a docstring following the Google Python Style Guide or NumPy Docstring Standard.
Content:
- Description: Briefly describe what the function or class does.
- Args: List and describe each parameter.
- Returns: Describe the return value(s).
- Raises: List any exceptions that are raised.

Example:

def calculate_mean(values: List[float]) -> float:
    """
    Calculates the mean of a list of numbers.

    Args:
        values (List[float]): A list of numerical values.

    Returns:
        float: The mean of the input values.

    Raises:
        ValueError: If the input list is empty.
    """
    if not values:
        raise ValueError("The input list is empty.")
    return sum(values) / len(values)

Documentation: Update or create documentation pages if your changes affect the public API.

Testing

Required: All new features and bug fixes must include appropriate unit tests.
Framework: Use unittest, pytest, or a similar testing framework.
Test Location: Place tests in the tests/ directory, mirroring the structure of swarms/.
Test Coverage: Aim for high test coverage to ensure code reliability.
Running Tests: Provide instructions for running tests.
```
pytest tests/
```

Code Style

PEP 8 Compliance: Follow PEP 8 style guidelines.
Linting Tools: Use flake8, black, or pylint to check code style.
Consistency: Maintain consistency with the existing codebase.

Areas Needing Contributions

We have several areas where contributions are particularly welcome.

Writing Tests

Goal: Increase test coverage to ensure the library's robustness.
Tasks:
- Write unit tests for existing code in swarms/.
- Identify edge cases and potential failure points.
- Ensure tests are repeatable and independent.

Improving Documentation

Goal: Maintain clear and comprehensive documentation for users and developers.
Tasks:
- Update docstrings to reflect any changes.
- Add examples and tutorials in the examples/ directory.
- Improve or expand the content in the docs/ directory.

Creating Multi-Agent Orchestration Methods

Goal: Provide new multi-agent orchestration methods

Community and Support

Communication: Engage with the community by participating in discussions on issues and pull requests.
Respect: Maintain a respectful and inclusive environment.
Feedback: Be open to receiving and providing constructive feedback.

License

By contributing to swarms, you agree that your contributions will be licensed under the MIT License.

Thank you for contributing to swarms! Your efforts help make this project better for everyone.

If you have any questions or need assistance, please feel free to open an issue or reach out to the maintainers.

Spaces:

patrickbdevaney
/

sw-api

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