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import base64
from pathlib import Path

from agno.agent import Agent
from agno.run.agent import RunOutput
from agno.tools.openai import OpenAITools
from agno.utils.media import download_file, save_base64_data

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------


# Example 1: Transcription
url = "https://agno-public.s3.amazonaws.com/demo_data/sample_conversation.wav"

local_audio_path = Path("tmp/sample_conversation.wav")

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    print(f"Downloading file to local path: {local_audio_path}")
    download_file(url, local_audio_path)

    transcription_agent = Agent(
        tools=[OpenAITools(transcription_model="gpt-4o-transcribe")],
        markdown=True,
    )
    transcription_agent.print_response(
        f"Transcribe the audio file for this file: {local_audio_path}"
    )

    # Example 2: Image Generation
    agent = Agent(
        tools=[OpenAITools(image_model="gpt-image-1")],
        markdown=True,
    )

    response = agent.run(
        "Generate an image of a sports car and tell me its color.", debug_mode=True
    )

    if isinstance(response, RunOutput):
        print("Agent response:", response.content)
        if response.images:
            image_base64 = base64.b64encode(response.images[0].content).decode("utf-8")
            save_base64_data(image_base64, "tmp/sports_car.png")

​
Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/91_tools/models

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

python openai_tools.py
For details, see OpenAI cookbook.