TinyAuton provides a minimal, extensible architecture for building autonomous agents that plan, execute, and refine tasks using OpenAI’s GPT models. It offers built-in modules for defining objectives, managing conversation context, invoking custom tools, and logging agent decisions. Through iterative self-reflection loops, the agent can analyze outcomes, adjust plans, and retry failed steps. Developers can integrate external APIs or local scripts as tools, set up memory or state, and customize the agent’s reasoning pipeline. TinyAuton is optimized for rapid prototyping of AI-driven workflows, from data extraction to code generation, all within a few lines of Python.

AgentUniverse provides a unified Python SDK to design, orchestrate, and run autonomous AI agents. Developers can define agent behaviors, integrate external tools or APIs, maintain conversational memory, and sequence multi-step tasks. Supporting LangChain, custom tool plugins, and configurable runtime environments, it accelerates agent development and deployment. Built-in monitoring and logging enable real-time insights, while its modular architecture allows easy extension with new capabilities or AI models.