Pydantic AI vs AutoGen

Pydantic AI is a framework built on the popular Python library Pydantic, designed to improve reliability and safety when working with large language models.

It provides structured data validation for LLM outputs, ensuring responses conform to predefined schemas and reducing errors in production environments.

Pydantic AI enables developers to build applications where LLMs produce consistent, machine-usable outputs rather than unstructured text. This is particularly useful for workflows like API responses, database inputs, or structured reporting.

AutoGen is an open-source framework developed by Microsoft for building multi-agent AI systems and advanced LLM-powered applications.

It enables developers to create autonomous agents that can collaborate, converse, and solve problems together, or with human feedback integrated into the loop.

AutoGen provides abstractions for defining roles, tasks, and communication protocols between agents, allowing flexible setups from simple assistants to complex, multi-agent ecosystems.

It is designed for rapid prototyping as well as production deployment, with features like conversation orchestration, human-AI collaboration, and tool integration.