LiteLLM Image Agent Bytes

image_agent_bytes.py

"""
Litellm Image Agent Bytes
=========================

Cookbook example for `litellm/image_agent_bytes.py`.
"""

from pathlib import Path

from agno.agent import Agent
from agno.media import Image
from agno.models.litellm import LiteLLM
from agno.tools.websearch import WebSearchTools
from agno.utils.media import download_image

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

agent = Agent(
    model=LiteLLM(id="gpt-5.6-luna"),
    tools=[WebSearchTools()],
    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 and give me the latest news about it.",
    images=[
        Image(content=image_bytes),
    ],
    stream=True,
)

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

if __name__ == "__main__":
    pass

Run the Example

Set up your virtual environment

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

Install dependencies

uv pip install -U agno ddgs litellm

Set your OpenAI credentials

Use an OpenAI API key with access to the requested model. The LiteLLM SDK calls the provider directly. An existing LITELLM_API_KEY overrides provider-specific credentials, so clear it for this example.

unset LITELLM_API_KEY
export OPENAI_API_KEY="your_provider_api_key_here"

Set compatible sampling options

Add temperature=None, top_p=None to every LiteLLM(...) using id="gpt-5.6-luna" or id="openai/gpt-5.6-luna" in your saved file. The adapter defaults to temperature=0.7 and top_p=1.0; the LiteLLM SDK rejects those sampling settings for this model's default reasoning mode before sending a request.

Run the example

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

python image_agent_bytes.py

Full source: cookbook/90_models/litellm/image_agent_bytes.py