​
Code

cookbook/models/ibm/watsonx/image_agent_bytes.py
from pathlib import Path

from agno.agent import Agent
from agno.media import Image
from agno.models.ibm import WatsonX
from agno.tools.duckduckgo import DuckDuckGoTools

agent = Agent(
    model=WatsonX(id="meta-llama/llama-3-2-11b-vision-instruct"),
    tools=[DuckDuckGoTools()],
    markdown=True,
)

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

# Read the image file content as bytes
with open(image_path, "rb") as img_file:
    image_bytes = img_file.read()

agent.print_response(
    "Tell me about this image and give me the latest news about it.",
    images=[
        Image(content=image_bytes),
    ],
    stream=True,
)

​
Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Set your API key

export IBM_WATSONX_API_KEY=xxx
export IBM_WATSONX_PROJECT_ID=xxx
3

Install libraries

pip install -U ibm-watsonx-ai ddgs agno
4

Add sample image

Place a sample image named “sample.jpg” in the same directory as the script.
5

Run Agent

python cookbook/models/ibm/watsonx/image_agent_bytes.py
This example shows how to use IBM WatsonX with vision capabilities. It loads an image from a file and passes it to the model along with a prompt. The model can then analyze the image and provide relevant information. Note: This example uses a vision-capable model (meta-llama/llama-3-2-11b-vision-instruct) and requires a sample image file.