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.

AI Agent Code Generator provides a command-line interface to scaffold Python projects for AI agents. Users select from multiple LangChain-based templates, configure their OpenAI API keys, and specify custom tools or functions. The tool then generates boilerplate code, project structure, and sample scripts to deploy conversational, information-retrieval, or task-automation agents. Developers can extend the generated code with additional plugins, modify prompts, and integrate new toolkits for specialized agent behavior, accelerating prototype and production development.