AutoGen

AutoGen is an open-source programming framework designed for building agentic AI applications where multiple autonomous agents collaborate to accomplish complex tasks. Developed by Microsoft, it provides a structured environment for creating, orchestrating, and managing conversations among AI agents powered by large language models (LLMs). The framework enables developers to define agents with distinct roles, capabilities, and communication protocols, allowing them to interact in a dynamic, multi-turn dialogue to solve problems ranging from code generation and data analysis to decision-making and workflow automation. At its core, AutoGen simplifies the construction of agent-based systems by offering abstractions for agent creation, message passing, and task delegation. Agents can be configured to use different LLM backends (e.g., GPT-4, GPT-3.5, Llama, or custom models), access external tools like web search or APIs, execute code in sandboxed environments, and remember conversation history for context-aware reasoning. The framework supports both fully autonomous agent teams and human-in-the-loop scenarios, where a human can step in to provide guidance, approve actions, or clarify ambiguous instructions. A key feature is its flexible conversation management. Developers can define custom workflows where agents initiate, pause, resume, or terminate dialogues based on conditions. For instance, a coding task can be split into a planner agent that designs the solution, a coder agent that writes the code, an executor agent that runs tests, and a reviewer agent that checks for errors—all communicating through a shared message bus. AutoGen also handles error recovery, retries, and fallback strategies, making it suitable for production-level automation. The framework includes bui