Overview of Agno (formerly Phidata) for Agents
Overview of Agno (formerly Phidata): an open-source, high-performance Python framework for building multi-modal AI agents and multi-agent systems.
Agno, formerly known as Phidata, is an open-source Python framework for building AI agents and multi-agent systems. It focuses on giving developers a fast, model-agnostic way to create agents with memory, knowledge, tools, and reasoning. This overview explains what Agno is, how it evolved from Phidata, and what it offers.
What Agno Is
Agno is a high-performance, open-source Python framework for building AI agents and teams of agents. Its core purpose is to let developers go from an idea to a working multi-agent system in relatively few lines of code, while keeping the framework lightweight and fast. It abstracts away much of the complexity of function calling, so developers can pass ordinary Python functions as tools and let the framework handle the details of invoking them.
The project began life as Phidata, a developer tool for building retrieval-augmented and tool-using assistants. It later rebranded to Agno, a change that reflected a shift in focus away from the original data-and-retrieval framing toward a runtime designed for production multi-agent systems. The framework is released under a permissive open-source license.
Multi-Modal and Multi-Agent
Two themes stand out in Agno's design. The first is multi-modality: agents can work across text, images, audio, and video rather than being limited to text alone, which broadens the range of applications developers can build. The second is multi-agent orchestration: Agno makes it straightforward to compose several specialized agents into teams that collaborate on a problem, with one agent able to delegate to others.
These capabilities are paired with the building blocks agents typically need—memory, knowledge integration, tool use, and reasoning. The result is a framework that can handle both a single focused agent and a coordinated group of agents working together, without requiring developers to assemble those pieces from scratch.
Performance and AgentOS
Agno places a notable emphasis on performance. It is designed to instantiate agents quickly and run efficiently, which matters when an application spins up many agents or handles concurrent workloads. This focus on speed and low overhead is one of the qualities the project highlights as distinguishing it from heavier frameworks.
For production, Agno includes AgentOS, a runtime layer that wraps agents, teams, and workflows in a server with session management and monitoring. This gives developers a path from local development to a deployable service with the operational features production systems require, rather than leaving deployment as an exercise for the developer.
Who It Is For
Agno is aimed at Python developers who want a fast, model-agnostic framework for building agents and multi-agent systems with minimal boilerplate. Its multi-modal support and team orchestration make it suitable for applications that go beyond simple text chat. As an open-source project, it can be adopted freely, with the AgentOS runtime available for teams that want a more production-oriented deployment story.
Frequently Asked Questions
Is Agno the same as Phidata?
Yes. Agno is the rebranded continuation of the Phidata project. The rename accompanied a shift in focus toward production multi-agent systems.
What does multi-modal mean in Agno?
It means Agno agents can work with more than just text, handling inputs and outputs across modalities such as images, audio, and video.
What is AgentOS?
AgentOS is Agno's production runtime layer that wraps agents, teams, and workflows in a server with session management and monitoring, providing a path from development to deployment.