> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Basic Agent

> Create a minimal agent with an OpenAIResponses model and print a streamed response.

Basic Agent Quickstart.

```python basic_agent.py theme={null}
"""
Basic Agent
=============================

Basic Agent Quickstart.
"""

from agno.agent import Agent
from agno.models.openai import OpenAIResponses

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
    name="Quickstart Agent",
    model=OpenAIResponses(id="gpt-5.2"),
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    agent.print_response(
        "Say hello and introduce yourself in one sentence.", stream=True
    )
```

## Run the Example

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

**1. Install dependencies**

```bash theme={null}
uv pip install -U agno openai
```

**2. Export your OpenAI API key**

```bash Mac/Linux theme={null}
export OPENAI_API_KEY="your_openai_api_key_here"
```

```bash Windows theme={null}
$Env:OPENAI_API_KEY="your_openai_api_key_here"
```

**3. Run the example**

Save the code above as `basic_agent.py`, then run:

```bash theme={null}
python basic_agent.py
```

Full source: [cookbook/02\_agents/01\_quickstart/basic\_agent.py](https://github.com/agno-agi/agno/blob/v3.0.4/cookbook/02_agents/01_quickstart/basic_agent.py)


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