Azure Image Agent Bytes

Migrate an Azure AI Foundry image-bytes agent from retired Llama 3.2 Vision to Llama 4 Scout.

The source-fidelity code uses a retired Azure AI Foundry model. Replace it with Llama 4 Scout before running the example.

Microsoft retired Llama-3.2-11B-Vision-Instruct on June 13, 2026. Deploy Llama-4-Scout-17B-16E-Instruct, point AZURE_ENDPOINT at that deployment, and replace the model ID before running. See the Azure model retirement schedule.

This source uses Agno's classic AzureAIFoundry adapter and the azure-ai-inference package, which Microsoft retired on August 26, 2026. Existing endpoint availability is separate from SDK retirement. For a new integration, use the current Foundry API setup with a compatible deployment. The classic setup below applies only to an existing compatible endpoint unless a current adaptation is explicitly provided.

image_agent_bytes.py
"""
Azure Image Agent Bytes
=======================

Cookbook example for `azure/ai_foundry/image_agent_bytes.py`.
"""

from pathlib import Path

from agno.agent import Agent
from agno.media import Image
from agno.models.azure import AzureAIFoundry
from agno.utils.media import download_image

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

agent = Agent(
    model=AzureAIFoundry(id="Llama-3.2-11B-Vision-Instruct"),
    markdown=True,
)

image_path = Path(__file__).parent.joinpath("sample.jpg")

download_image(
    url="https://upload.wikimedia.org/wikipedia/commons/0/0c/GoldenGateBridge-001.jpg",
    output_path=str(image_path),
)

# Read the image file content as bytes
image_bytes = image_path.read_bytes()

agent.print_response(
    "Tell me about this image.",
    images=[
        Image(content=image_bytes),
    ],
    stream=True,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass

Run the Classic Example

Set up your virtual environment

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

Install dependencies

uv pip install -U agno aiohttp azure-ai-inference

Export environment variables

export AZURE_API_KEY="your_azure_api_key_here"
export AZURE_ENDPOINT="your_azure_endpoint_here"

Use Llama 4 Scout

Deploy Llama-4-Scout-17B-16E-Instruct, update AZURE_ENDPOINT, and replace Llama-3.2-11B-Vision-Instruct in the saved file.

Run the example

Save the code above as image_agent_bytes.py, then run:

python image_agent_bytes.py

Full source: cookbook/90_models/azure/ai_foundry/image_agent_bytes.py