p3ngu1nzz / agentnet Goto Github PK

2.0 2.0 0.0 28 KB

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.

License: MIT License

C++ 72.73% CMake 27.27%

agentnet's Introduction

Hi there 👋

I’m p3ngu1nZz, a passionate gamer and developer working on a cat game engine written with Meow. I’m working on creating fun and immersive cat games using Meow, C++, and WebAssembly. I also love to contribute to open source projects and learn new technologies. 😊

Summary

Experienced and versatile software engineer with over 15 years of experience in various domains such as game development, AI, web development, and cloud computing.
Skilled in multiple programming languages, frameworks, and tools such as Java, C#, C++, Python, Unity, Unreal, ExtJS, GWT, NodeJS, PyTorch, and more.
Passionate about creating innovative and engaging solutions that solve real-world problems and delight users.

Skills

Artifical Intelligence

AI Operator
AI Scientist
ML Trainer
Robotist
Cybernetics

Programming Languages

C#, C, Cpp
Python
Java/JavaScript\
Dragon

Game Engines

Unity
Unreal

Tools

ML-Agents
PyTorch
TensorFlow
NodeJS
Electron
Dragon

IDEs / Editors

Visual Studio
Nano
Vi/m

agentnet's People

Contributors

Stargazers

Watchers

agentnet's Issues

User Feedback Collection

Implement a system for collecting user feedback on the new chat completion feature. This could be through surveys, direct feedback in the application, or monitoring usage patterns.

Future Roadmap

Discuss and plan the future roadmap of your project post-integration of the LLaMa models. Consider what features or improvements could come next.

Community Engagement

discuss strategies for engaging with your project’s community. This could include forums, social media, or other platforms where users and developers can interact.

Testing Framework

consider setting up a testing framework for the new chat completion feature. This could include unit tests, integration tests, and end-to-end tests to ensure the feature works correctly and is robust against various input scenarios.

Security Review

Given that you’re working with AI models, it’s important to review the security aspects of your application, especially how user data is handled and stored.

Integrate LLaMa Model for Chat Completion in AgentNetTerm

Issue Description

We're exploring the integration of the LLaMa model into our AgentNetTerm console application to enable chat completion capabilities. This task involves setting up the LLaMa model within our C++ environment, ensuring compatibility, and creating a seamless user experience for chat interactions.

Goals:

Successfully integrate the LLaMa model with our existing C++ project.
Develop a chat interface that can handle input and output for chat completion.
Implement an inference engine to process and respond to user inputs using the LLaMa model.

Steps:

Review llamacpp documentation and examples for integration guidance.
Set up the necessary environment for running the LLaMa model.
Convert and place the downloaded LLaMa models into the llama sources directory.
Build and test the integration with a simple chat completion example.
Document the process and any issues encountered for team reference.

Expected Outcome:

A proof of concept demonstrating the LLaMa model's chat completion in our AgentNetTerm application, paving the way for more advanced AI features in our project.