Multi-Agent System provides a lightweight yet powerful toolkit for designing and executing multi-agent simulations. Users can create custom Agent classes to encapsulate decision-making logic, define Environment objects to represent world states and rules, and configure a Simulation engine to orchestrate interactions. The framework supports modular components for logging, metrics collection, and basic visualization to analyze agent behaviors in cooperative or adversarial settings. It’s suitable for rapid prototyping of swarm robotics, resource allocation, and decentralized control experiments.

Duet GPT is a Python-based open source framework for orchestrating multi-agent conversations between two GPT models. You define distinct agent roles, customized with system prompts, and the framework manages turn-taking, message passing, and conversation history automatically. This cooperative structure accelerates complex task resolution, enabling comparative reasoning, critique cycles, and iterative refinement through back-and-forth exchanges. Its seamless OpenAI API integration, simple configuration, and built-in logging make it ideal for research, prototyping, and production workflows in coding assistance, decision support, and creative ideation. Developers can extend the core classes to integrate new LLM services, adjust the iterator logic, and export transcripts in JSON or Markdown formats for post-analysis.

Logmind is an advanced AI agent designed to analyze log files using machine learning algorithms. It automatically detects anomalies, patterns, and generates insights that help developers and system administrators troubleshoot issues faster. By providing real-time alerts and recommendations, Logmind enables users to optimize their log management processes and improve the reliability of their systems.