The Multi-Agent System Framework offers a modular structure for building and orchestrating multiple AI agents within Python applications. It includes an agent manager to spawn and supervise agents, a communication backbone supporting various protocols (e.g., message passing, event broadcasting), and customizable memory stores for long-term knowledge retention. Developers can define distinct agent roles, assign specialized tasks, and configure cooperative strategies such as consensus-building or voting. The framework integrates seamlessly with external AI models and knowledge bases, enabling agents to reason, learn, and adapt. Ideal for distributed simulations, conversational agent clusters, and automated decision-making pipelines, the system accelerates complex problem solving by leveraging parallel autonomy.

Reworkd is a cutting-edge AI technology designed to revolutionize content creation and workflow automation. This platform leverages advanced AI to enable users to extract structured web data efficiently and automate various business processes. Its capabilities include generating and repairing web extractors on the fly, enabling businesses to save time and resources, and ensuring high-quality data extraction. Whether it's developing custom AI agents or automating mundane tasks, Reworkd streamlines processes for better productivity and efficiency.