> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Agents

> Build and configure agents visually in AgentOS Studio.

Build production-grade agents via AgentOS Studio’s visual canvas. Wire up models, tools,
and structured I/O into complex agentic workflows. Deploy instantly. No-code required.

## Creating Agents

Create a new agent by selecting components from your [Registry](/agent-os/studio/registry) and configuring them in the properties panel:

| Setting                 | Description                                      |
| ----------------------- | ------------------------------------------------ |
| **Model**               | Select from registered models                    |
| **Tools**               | Attach registered tools and toolkits             |
| **Instructions**        | System-level instructions for the agent          |
| **Input/Output Schema** | Structured I/O using registered Pydantic schemas |
| **Memory**              | Enable memory for multi-turn conversations       |
| **Knowledge**           | Attach knowledge bases for RAG                   |

<Tip>
  Switch to the advanced JSON config editor for fine-grained control over agent settings.
</Tip>

## Using Agents

Use Studio-built Agents in multiple ways:

* **Chat directly** with the agent via the Chat page
* **Add to Teams** for multi-agent collaboration
* **Use in Workflows** as step executors for automation pipelines

## Save and Run

Once your agent is configured:

1. **Save** your agent to persist it to the registry
2. Navigate to the **Chat page** to interact with your agent
3. Send messages and receive responses in real-time
4. View tool calls, reasoning, and outputs as the agent works

## Code Equivalent

Agents built in Studio are native instances of the 'Agent' class in the SDK.

```python theme={null}
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.tools.websearch import WebSearchTools

agent = Agent(
    name="Research Agent",
    model=OpenAIChat(id="gpt-5-mini"),
    tools=[WebSearchTools()],
    instructions="Research topics thoroughly using web search.",
    markdown=True,
)
```

## Developer Resources

* [Agent reference](/reference/agents/agent)
* [Building agents](/agents/building-agents)
* [Studio Registry](/agent-os/studio/registry)