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

# Audio Model Output

> Get audio output from model responses in Agno agents.

Similar to providing audio inputs, you can also get audio outputs from an agent. Take a look at the [compatibility matrix](/models/compatibility#multimodal-support) to see which models support audio as output.

## Audio response modality

The following example demonstrates how some models can directly generate audio as part of their response.

```python audio_agent.py theme={null}
from agno.agent import Agent, RunOutput
from agno.models.openai import OpenAIChat
from agno.utils.audio import write_audio_to_file

agent = Agent(
    model=OpenAIChat(
        id="gpt-audio",
        modalities=["text", "audio"],
        audio={"voice": "alloy", "format": "wav"},
    ),
    markdown=True,
)
response: RunOutput = agent.run("Tell me a 5 second scary story")

# Save the response audio to a file
if response.response_audio is not None:
    write_audio_to_file(
        audio=response.response_audio.content, filename="tmp/scary_story.wav"
    )
```

<Check>
  You can find the audio response in the `RunOutput.response_audio` object.
</Check>

<Note>
  There is a distinction between audio response modality and generated audio artifacts. When the model responds with audio, it is stored in the `RunOutput.response_audio` object. The generated audio artifacts are stored in the `RunOutput.audio` list.
</Note>

## Audio input and Audio output

The following example demonstrates how to provide a combination of audio and text inputs to an agent and obtain both text and audio outputs.

```python audio_agent.py theme={null}
import requests
from agno.agent import Agent
from agno.media import Audio
from agno.models.openai import OpenAIChat
from agno.utils.audio import write_audio_to_file
from rich.pretty import pprint

# Fetch the audio file and convert it to a base64 encoded string
url = "https://openaiassets.blob.core.windows.net/$web/API/docs/audio/alloy.wav"
response = requests.get(url)
response.raise_for_status()
wav_data = response.content

agent = Agent(
    model=OpenAIChat(
        id="gpt-audio",
        modalities=["text", "audio"],
        audio={"voice": "sage", "format": "wav"},
    ),
    markdown=True,
)

run_response = agent.run(
    "What's in these recording?",
    audio=[Audio(content=wav_data, format="wav")],
)

if run_response.response_audio is not None:
    pprint(run_response.content)
    write_audio_to_file(
        audio=run_response.response_audio.content, filename="tmp/result.wav"
    )
```

## Usage

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

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

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```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"
      ```
    </CodeGroup>
  </Step>

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