Plugboard, a Python framework for event-driven modeling and orchestration, enables simulation of complex processes with AI integration and cloud scalability.

Plugboard is an event-driven modeling and orchestration framework in Python that allows users to define models and connect components so data automatically moves between them; models can scale from a laptop to multiple processors or cloud compute clusters via Ray framework integration.

The framework supports discrete time and event-based simulation paradigms, built-in LLM integrations with support for multiple providers, YAML model specification format for reproducibility, and detailed component logging for monitoring and surrogate modeling; it requires Python >= 3.12 and integrates with cloud storage, SQL databases, and cloud providers (AWS, Azure, GCP).

Users can describe desired models in natural language to AI coding assistants (GitHub Copilot, Cursor, Claude, etc.), which generate working Plugboard code using auto-generated context; the framework is designed to handle data-intensive industrial process simulation including material recirculation and composition from physics-based, machine-learning, and AI components.