mini-agi is designed to simplify the creation of autonomous AI agents by providing a minimal, modular framework. Built in Python, it leverages OpenAI’s language models to interpret high-level goals, decompose them into sub-tasks, and orchestrate tool calls such as HTTP requests, file operations, or custom actions. The framework includes memory storage to track agent state and results, a planner module for task decomposition with cost-based heuristics, and an executor module that sequentially invokes tools. With configuration files, users can inject custom tools, define prompt templates, and adjust planning depth. mini-agi’s lightweight architecture makes it ideal for prototyping AI agents that perform research queries, automate workflows, or generate code autonomously.