Augmented Generative Intelligence Framework The ezAGI project is an advanced augmented generative intelligence system that combining various components to create a robust, flexible, and extensible framework for reasoning, decision-making, self-healing, and multi-model interaction. Core Components MASTERMIND Purpose:The mastermind module serves as the core orchestrator for the easyAGI system. It manages agent lifecycles, integrates various components, and ensures the overall health and performance of the system. Key Features: SimpleCoder Purpose:The SimpleCoder module defines a coding agent […]

ezAGI fundamental Augmented General Intelligence draw_conclusion(self) method The draw_conclusion method is designed to synthesize a logical conclusion from a set of premises, validate this conclusion, and then save the input/response sequence to a short-term memory storage. This function is a critical component in the context of easy Augmented General Intelligence (AGI) system, as it demonstrates the ability to process information, generate responses, validate outputs, and maintain a record of interactions for future reference and learning. […]

putting the fun into a fundamental augmented general intelligence framework as funAGI funAGI is a development branch of easyAGI. easyAGI was not being easy and SimpleMind neural network was proving to not be simple. For that reason is was necessary to remove reasoning.py and take easyAGI back to its roots of BDI Socratic Reasoning from belief, desire and intention. So this back to basics release should be taken as a verbose logging audit of SocraticReasoning […]