# Agno

> A Python framework for building multi-agent systems with memory, knowledge, and tools — formerly Phidata, now with the AgentOS runtime.

Agno (formerly Phidata) is a Python framework for building multi-agent systems with memory, knowledge, and tools. You compose Agents, Teams, and Workflows over 20+ model providers, and can run them in production with the AgentOS runtime. The core library is open source under Apache-2.0.

Website: https://agno.com

Agno is a **Python framework for building multi-agent systems** with memory, knowledge, and tools. It was formerly known as **Phidata** and was renamed to Agno in early 2025, with its GitHub organization moving to `agno-agi`. You compose three core abstractions — Agents, Teams, and Workflows — over 20+ model providers, and the framework is model-agnostic so you can swap providers without rewriting agent logic.

It is aimed at developers who want to go beyond a single prototype agent to a managed platform: the project pairs the open-source SDK with **AgentOS**, a FastAPI-based runtime for serving agents in production with tracing, scheduling, and RBAC. That makes it a fit for an AI-assisted workflow where you scaffold agents locally and then run them as a real service.

## Highlights

- **Agents, Teams, Workflows** — build a single tool-using agent, coordinate a team of specialists, or wire deterministic step-based workflows from the same SDK.
- **Memory and knowledge** — attach session memory and knowledge stores (backed by common vector databases) so agents retain context and ground answers in your data.
- **Tools and integrations** — give agents tools through a large library of prebuilt toolkits, or register your own Python functions.
- **AgentOS runtime** — serve agents as a production service with tracing, scheduling, RBAC, and a control plane that runs in your own cloud.

## In an AI-assisted workflow

Use Agno to define a tool-equipped agent in a few lines, then iterate with your coding assistant before promoting it to AgentOS. See [Agent Frameworks in 2026](/guides/concepts/agent-frameworks-2026) for where it sits among the alternatives.

```python
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.duckduckgo import DuckDuckGoTools

agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    tools=[DuckDuckGoTools()],
    markdown=True,
)
agent.print_response("Summarize the latest news on agent frameworks")
```

> [!TIP]
> Start with a single Agent, then graduate to a Team or Workflow only when one agent's responsibilities clearly split. Verify import paths and class names against the current docs, since Agno's API changed across the 2.0 release.

## Good to know

The core Agno library is open source under Apache-2.0 and free to self-host — you supply your own model provider and database. A free control-plane tier plus paid Pro and Enterprise plans (AgentOS) add hosted management, live connections, retention, and team seats; confirm the current tiers and limits on the official pricing page before relying on them. For patterns on coordinating multiple agents, see [Multi-Agent Orchestration](/guides/advanced/multi-agent-orchestration).

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_Source: https://agentscamp.com/tools/agno — Tool on AgentsCamp._