p3ngu1nzz / agentnet

AgentNet is a state-of-the-art peer-to-peer networking framework designed for decentralized agent systems. It utilizes Vulkan for high-performance graphics rendering, enabling efficient communication and data sharing among distributed agents.

AgentNet

AgentNet is a sophisticated peer-to-peer networking framework that empowers distributed agents to communicate and share data with high efficiency. Leveraging Vulkan for graphics rendering, AgentNet is built for performance and scalability, providing a robust platform for decentralized agent interactions.

Getting Started

These instructions will guide you through getting a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

Before you begin, ensure you have the following installed:

• Vulkan SDK
• CMake
• A C++ compiler like GCC or Clang
• Access to Llama sources (see below)

Llama Sources

To build this project from source, you will need access to the Llama sources. Follow these steps to download them:

1. Visit the Llama GitHub repository and follow the instructions to register and accept the license¹.
2. Once approved, you will receive a custom URL via email from Meta.
3. Clone the Llama repository and run the download.sh script with the custom URL provided. (Requires Linux or MacOS)

Installation

Follow these steps to set up your development environment:

1. Clone the repository:

git clone https://github.com/K-Rawson/AgentNet.git

2. Navigate to the project directory:

cd AgentNet

3. Create a build directory:

mkdir build && cd build

4. Run CMake to configure the project:

cmake ..

5. Build the project:

cmake --build .

Running the Tests

To run the automated tests for this system, use the following command:

ctest

Deployment

For deployment, additional steps may be required, such as setting up a server environment or configuring network settings.

Built With

• Vulkan - A low-overhead, cross-platform 3D graphics and compute API.
• CMake - An open-source, cross-platform family of tools designed to build, test, and package software.
• Llama - For building AgentNet llama models from source. (Advanced)

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

• K-Rawson - Initial work - AgentNet

See also the list of contributors who participated in this project.

License

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

Acknowledgments

• Tonic-AI

Please cite this project as:

Rawson, K. (2024). AgentNet: An Innovative AI Framework for Gaming. [https://github.com/K-Rawson/AgentNet](https://github.com/K-Rawson/AgentNet)