Agno

Agno is an open-source Python framework for building AI agents that instantiates agents in ~3 microseconds — 5,000x faster than LangGraph — while using ~5KB of memory per agent. Formerly known as Phidata, it was rebranded in January 2025 and now has 39,100+ GitHub stars. You can ship a production-ready agent with memory and tools in under 20 lines of Python. What Is Agno? The Phidata Rebrand Explained Agno is a high-performance, model-agnostic Python framework for building AI agents and multi-agent systems, formerly distributed under the name Phidata until January 2025. The rebrand was deliberate: “Phidata” had become associated with data engineering pipelines, while the team’s actual focus had shifted entirely to agentic systems. The new name comes from the ancient Greek word ἁγνὸ (agno), meaning “pure” — reflecting the framework’s philosophy of a clean, minimal API that avoids the orchestration bloat common in rival frameworks. Agno is developed by a small core team and backed by a fast-growing open-source community that crossed 39,100 GitHub stars in March 2026, making it one of the fastest-growing AI agent libraries in Python. The framework is structured around three layers: the SDK (the Python library developers use), AgentOS (a managed runtime for production deployment), and a Control Plane UI for monitoring agent sessions and traces. Nothing in Agno’s design requires a specific LLM provider — it supports OpenAI, Anthropic Claude, Google Gemini, Mistral, and local Ollama models out of the box. Unlike LangGraph’s graph-based orchestration or CrewAI’s role-based crew model, Agno prioritizes raw performance and simplicity, letting developers compose agents without being forced into a particular mental model. ...