kintsay

"Eat your greens and stay smart!"

Description

Leverage the power of Celery and SmolAgents in this Python project. Build scalable, distributed workflows with intelligent agents that handle tasks efficiently and asynchronously.

This project provides a powerful foundation for building scalable, asynchronous systems by combining:

• Celery: For reliable task queuing and management.
• SmolAgents: For creating intelligent, autonomous agents to perform tasks.
• Python: The flexible language that ties everything together.

Features

• [Feature 1 - e.g., Asynchronous task processing with Celery]
• [Feature 2 - e.g., Creation of custom SmolAgents with flexible configurations]
• [Feature 3 - e.g., Scalable architecture for handling large volumes of tasks]
• [Feature 4 - e.g., Easy integration with various message brokers (e.g., RabbitMQ, Redis)]
• [Feature 5 - e.g., Customizable agent workflows and task pipelines]
• [Feature 6 - e.g., Optional integrations with other libraries/services]

Getting Started

Prerequisites

• Python 3.10 or higher
• [Specify required Celery version, e.g., Celery 5.2+]
• [Specify required Redis or RabbitMQ version, e.g., Redis 6.0 or RabbitMQ 3.8+]
• pip package manager

Installation

1. Clone the repository:

   git clone /github.com/rpfilomeno/kintsay
   cd kintsay

2. Create and activate a virtual environment (recommended):

   python -m venv venv
   source venv/bin/activate  # On Linux/macOS
   # venv\Scripts\activate  # On Windows

3. Install the required packages:

   pip install -r requirements.txt

Configuration

1. Broker Setup:

   • Choose a message broker (e.g., Redis, RabbitMQ).

   #Example config in settings.py
   BROKER_URL = 'redis://localhost:6379/0'
   CELERY_RESULT_BACKEND = 'redis://localhost:6379/0'

2. Celery Configuration:

   #TODO

3. SmolAgents Setup:

# TODO

Running the Project

1. Start the Celery worker:

   celery -A kitsay.celery worker --loglevel=info

2. Run the Python application:

#TODO

Usage

• How to define a Celery task and trigger it asynchronously.

# TODO

• How to create a new SmolAgent and configure its behavior.

# TODO

• How to combine Celery tasks and agents for complex workflows.

# TODO

Contributing

Contributions are welcome! Please read our CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests.

License

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

Acknowledgments

This project heavily relies on the following open-source libraries:

• Celery: A distributed task queue used for asynchronous task processing. We thank the Celery team for providing such a powerful and reliable tool. [Link to Celery's website: https://docs.celeryq.dev/en/stable/index.html]
• SmolAgents: a smol library to build great agents! We acknowledge the contributions of the SmolAgents developers to the world of autonomous AI. https://github.com/huggingface/smolagents.

Citing kintsay

If you use kintsay in your publication, please cite it by using the following BibTeX entry.

@Misc{kintsay,
  title =        {`kintsay`: Eat your greens and stay smart.},
  author =       {Roger Filomeno},
  howpublished = {\url{https://github.com/rpfilomeno/kintsay}},
  year =         {2025}
}