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A multi-agent framework enabling the development of decentralized, collaborative systems with modular architecture for flexibility and extensibility.

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WORK IN PROGRESS

Pilet

Welcome to Pilet! 🚀

Pilet is an open-source agentic framework designed to help you create a local version of GPT-4o using any open-source model. With Pilet, you can leverage the power of state-of-the-art language models and customize them to suit your unique needs. Whether you're a researcher, developer, or enthusiast, Pilet provides the tools you need to build, fine-tune, and deploy powerful language models locally.

Key Features

  • Agentic Framework: Easily create and manage agents for various tasks.
  • Local GPT-4o: Build a local version of GPT-4o using open-source models.
  • Customization: Fine-tune models to meet your specific requirements.
  • Open-Source: Free to use and modify, with a growing community of contributors.

Getting Started

Prerequisites

  • Python 3.7+
  • PyTorch
  • Transformers library from Hugging Face

Installation

Clone the repository and install the necessary dependencies:

git clone https://github.com/yourusername/pilet.git
cd pilet
pip install -r requirements.txt

Usage

1. Load Your Model

First, load your preferred open-source model. Pilet supports a variety of models from the Hugging Face model hub.

from transformers import AutoModel, AutoTokenizer

model_name = "your-model-name"
model = AutoModel.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

2. Create an Agent

Create an agent using the Pilet framework. An agent is a modular component that can be used to perform specific tasks.

from pilet import Agent

class MyAgent(Agent):
    def __init__(self, model, tokenizer):
        self.model = model
        self.tokenizer = tokenizer

    def respond(self, prompt):
        inputs = self.tokenizer(prompt, return_tensors="pt")
        outputs = self.model(**inputs)
        return outputs

agent = MyAgent(model, tokenizer)

3. Use the Agent

Interact with your agent to get responses based on your prompts.

prompt = "What is the capital of France?"
response = agent.respond(prompt)
print(response)

Contributing

We welcome contributions from the community! If you'd like to contribute, please fork the repository and create a pull request. You can also open an issue to report bugs or request features.

Steps to Contribute

  1. Fork the repository
  2. Create a new branch (git checkout -b feature/your-feature)
  3. Commit your changes (git commit -m 'Add some feature')
  4. Push to the branch (git push origin feature/your-feature)
  5. Open a pull request

License

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


Happy coding! 💻✨


Pilet - Empowering your local language models.

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A multi-agent framework enabling the development of decentralized, collaborative systems with modular architecture for flexibility and extensibility.

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