> ## 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.

# Streaming Agent

> Stream a Llama-powered Agno agent's response as it's generated.

## Code

```python basic_stream.py theme={null}
from typing import Iterator  # noqa
from agno.agent import Agent, RunOutputEvent  # noqa
from agno.models.meta import Llama

agent = Agent(model=Llama(id="Llama-4-Maverick-17B-128E-Instruct-FP8"), markdown=True)

# Get the response in a variable
# run_response: Iterator[RunOutputEvent] = agent.run("Share a 2 sentence horror story", stream=True)
# for chunk in run_response:
#     print(chunk.content)

# Print the response in the terminal
agent.print_response("Share a 2 sentence horror story", stream=True)
```

## Usage

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

**1. Set your LLAMA API key**

```bash theme={null}
export LLAMA_API_KEY=YOUR_API_KEY
```

**2. Install dependencies**

```bash theme={null}
uv pip install llama-api-client agno
```

**3. Run Agent**

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


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