FastAPI vs. PydanticAI vs. Python vs. Rio Comparison Chart

PydanticAI is a Python-based agent framework designed to simplify the development of production-grade applications using generative AI. Built by the team behind Pydantic, the framework integrates seamlessly with popular AI models such as OpenAI, Anthropic, Gemini, and others. It offers type-safe design, real-time debugging, and performance monitoring through Pydantic Logfire. PydanticAI also provides structured responses by leveraging Pydantic to validate model outputs, ensuring consistency. The framework includes a dependency injection system to support iterative development and testing, as well as the ability to stream LLM outputs for rapid validation. It is ideal for AI-driven projects that require flexible and efficient agent composition using standard Python best practices. We built PydanticAI with one simple aim: to bring that FastAPI feeling to GenAI app development.

Rio is an open source Python framework that enables developers to build modern web and desktop applications entirely in Python. Inspired by frameworks like React and Flutter, Rio introduces a declarative UI model where components are defined as Python data classes with a build() method, allowing for reactive state management and seamless UI updates. It includes over 50 built-in components adhering to Google's Material Design, facilitating the creation of professional-grade interfaces. Rio's layout system is Pythonic and intuitive, calculating each component's natural size before distributing available space, eliminating the need for traditional CSS. Developers can run applications locally or in the browser with the backend powered by FastAPI and communication handled via WebSockets.