AIAgentWorkshop is an open-source Python project demonstrating how to build autonomous AI agents capable of planning, decision-making, and tool usage. It includes examples of integrating web search, file management, and system commands, along with simple memory and reasoning modules. Developers can follow guided exercises to create agents that interpret user goals, generate multi-step plans, execute tasks across different tools, and maintain context. The modular architecture makes it easy to swap or extend tools and chain agent actions for complex workflows, turning AI research concepts into runnable prototypes.

openai-agents-python is a comprehensive Python package designed to help developers construct fully autonomous AI agents. It provides abstractions for agent planning, tool integration, memory states, and execution loops. Users can register custom tools, specify agent goals, and let the framework orchestrate step-by-step reasoning. The library also includes utilities for testing and logging agent actions, making it easier to iterate on behaviors and troubleshoot complex multi-step tasks.

Aegix provides a robust SDK for orchestrating AI Agents capable of handling complex workflows through multi-step reasoning. With support for various LLM providers, it lets developers integrate custom tools—from database connectors to web scrapers—and maintain conversation state with memory modules such as vector stores. Aegix’s flexible agent loop architecture allows the specification of planning, execution, and review phases, enabling agents to refine outputs iteratively. Whether building document question-answering bots, code assistants, or automated support agents, Aegix simplifies development with clear abstractions, configuration-driven pipelines, and easy extension points. It’s designed to scale from prototypes to production, ensuring reliable performance and maintainable codebases for AI-driven applications.