> ## 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.

# Basic

> Create a basic AI agent with A2A interface

## Code

```python a2a_basic.py theme={null}
from agno.agent.agent import Agent
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS
from agno.os.interfaces.a2a import A2A

chat_agent = Agent(
    name="Assistant",
    model=OpenAIResponses(id="gpt-5.2"),
    instructions="You are a helpful AI assistant.",
    add_datetime_to_context=True,
    markdown=True,
)

agent_os = AgentOS(
    agents=[chat_agent],
    a2a_interface=True,
)
app = agent_os.get_app()

if __name__ == "__main__":
    agent_os.serve(app="a2a_basic:app", reload=True)
```

## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Set Environment Variables">
    ```bash theme={null}
    export OPENAI_API_KEY=your_openai_api_key
    ```
  </Step>

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno openai a2a-protocol
    ```
  </Step>

  <Step title="Run Example">
    ```bash theme={null}
    python a2a_basic.py
    ```
  </Step>
</Steps>

## Key Features

* **A2A Interface**: A2A compatible conversation experience
* **Real-time Chat**: Instant message exchange
* **Markdown Support**: Rich text formatting in responses
* **DateTime Context**: Time-aware responses
* **Open Protocol**: Compatible with A2A frontends