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.

Azure AI Foundry Agents Samples provides developers with a rich set of example scenarios that illustrate how to leverage Azure AI Foundry SDKs and services. It includes conversational agents with long-term memory, planner agents that break down complex tasks, tool-enabled agents that call external APIs, and multimodal agents combining text, vision, and speech. Each sample is preconfigured with environment setups, LLM orchestration, vector search, and telemetry to accelerate prototyping and deployment of robust AI solutions on Azure.