The Multi Agent Robotic System project offers a modular Python-based platform for developing, simulating, and deploying cooperative robotic teams. At its core, it implements decentralized control strategies, enabling robots to share state information and collaboratively allocate tasks without a central coordinator. The system includes built-in modules for path planning, collision avoidance, environment mapping, and dynamic task scheduling. Developers can integrate new algorithms by extending provided interfaces, adjust communication protocols via configuration files, and visualize robot interactions in simulated environments. Compatible with ROS, it supports seamless transitions from simulation to real-world hardware deployments. This framework accelerates research by providing reusable components for swarm behavior, collaborative exploration, and warehouse automation experiments.

Ollama Bot is a Node.js-based AI agent designed to run on Discord servers, leveraging the Ollama CLI and local LLM models for generating conversational responses. It establishes a persistent chat context, allowing users to maintain topic continuity over multiple messages. Administrators can define custom prompts, set model parameters, and restrict commands to specific roles. The bot supports multiple LLM models, automatically manages message queues for high throughput, and logs interactions for audit purposes. Installation involves cloning the repository, installing dependencies via npm, and configuring environment variables such as the Discord bot token and Ollama settings. Once deployed, the bot listens for slash commands, forwards queries to the Ollama model, and posts generated replies directly in Discord channels.