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This example demonstrates how to create an agent that can handle multi-turn audio conversations, maintaining context between audio interactions while generating both text and audio responses.

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Code

audio_multi_turn.py
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.utils.audio import write_audio_to_file
from rich.pretty import pprint

agent = Agent(
    model=OpenAIResponses(
        id="gpt-5.2-audio-preview",
        modalities=["text", "audio"],
        audio={"voice": "sage", "format": "wav"},
    ),
    add_history_to_context=True,
    db=SqliteDb(
        session_table="audio_multi_turn_sessions", db_file="tmp/audio_multi_turn.db"
    ),
)

run_response = agent.run("Is a golden retriever a good family dog?")
pprint(run_response.content)
if run_response.response_audio is not None:
    write_audio_to_file(
        audio=run_response.response_audio.content, filename="tmp/answer_1.wav"
    )

run_response = agent.run("What breed are we talking about?")
pprint(run_response.content)
if run_response.response_audio is not None:
    write_audio_to_file(
        audio=run_response.response_audio.content, filename="tmp/answer_2.wav"
    )

​
Usage

1

Set up your virtual environment

uv venv --python 3.12
source .venv/bin/activate
2

Install dependencies

uv pip install -U openai agno
3

Export your OpenAI API key

  export OPENAI_API_KEY="your_openai_api_key_here"
4

Run Agent

python audio_multi_turn.py