Llama OpenAI Image Input Bytes

This source imports native Llama despite its OpenAI-compatible location. Apply the compatible adapter instructions below to use the endpoint described by this page. The dedicated LlamaOpenAI adapter has a formatter mismatch at the linked revision.

image_input_bytes.py

"""
Meta Image Input Bytes
======================

Cookbook example for `meta/llama_openai/image_input_bytes.py`.
"""

from pathlib import Path

from agno.agent import Agent
from agno.media import Image
from agno.models.meta import Llama
from agno.tools.websearch import WebSearchTools
from agno.utils.media import download_image

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

agent = Agent(
    model=Llama(id="Llama-4-Maverick-17B-128E-Instruct-FP8"),
    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 llama-api-client openai

Export your Meta Llama API key

export LLAMA_API_KEY="your_llama_api_key_here"

Use the compatible API adapter

Replace the LlamaOpenAI import (or Llama in the byte-image source) with this helper. Then replace every LlamaOpenAI(...) or Llama(...) construction in the saved file with llama_model(...). Keep the existing id, temperature, and any retry options inside those calls.

Compatible model helper

from os import getenv

from agno.models.openai.like import OpenAILike


def llama_model(**kwargs):
    return OpenAILike(
        api_key=getenv("LLAMA_API_KEY"),
        base_url="https://api.llama.com/compat/v1/",
        supports_native_structured_outputs=False,
        supports_json_schema_outputs=True,
        **kwargs,
    )

This uses Meta's OpenAI-compatible endpoint. You need a Meta API account with access to the selected model; check your account's current model catalog before running.

Run the example

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

python image_input_bytes.py

Full source: cookbook/90_models/meta/llama_openai/image_input_bytes.py