Image to JSON: Multimodal Structured Output with Llama 3.2 Vision, MAX and Pydantic
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In this recipe, we will cover:
We'll walk through building a solution that showcases:
Let's get started.
Please make sure your system meets our system requirements.
To proceed, ensure you have the pixi
CLI installed:
curl -fsSL https://pixi.sh/install.sh | sh
...and updated to the latest version:
pixi self-update
For this recipe, you will need:
Set up your environment variables:
export HUGGING_FACE_HUB_TOKEN=
Structured output with MAX requires GPU access. For running the app on GPU, ensure your system meets these GPU requirements:
Download the code for this recipe:
git clone https://github.com/modularml/max-recipes.git
cd max-recipes/max-serve-multimodal-structured-output
Run the server with vision model:
Make sure the port 8010
is available. You can adjust the port settings in pyproject.toml.
pixi run server
This will start MAX with Llama 3.2 Vision and
Run the example code that extracts player information from a basketball image via:
pixi run main
The output will look like:
{
"players": [
{
"name": "Klay Thompson",
"number": 11
},
{
"name": "Stephen Curry",
"number": 30
},
{
"name": "Kevin Durant",
"number": 35
}
]
}
The core of our structured output system uses Pydantic models to define the expected data structure:
from pydantic import BaseModel
class Player(BaseModel):
name: str = Field(description="Player name on jersey")
number: int = Field(description="Player number on jersey")
class Players(BaseModel):
players: List[Player] = Field(description="List of players visible in the image")
How it works:
The application uses the OpenAI client to communicate with MAX:
from openai import OpenAI
client = OpenAI(api_key="local", base_url="http://localhost:8000/v1")
completion = client.beta.chat.completions.parse(
model="meta-llama/Llama-3.2-11B-Vision-Instruct",
messages=[
{"role": "system", "content": "Extract player information from the image."},
{"role": "user", "content": [
{
"type": "text",
"text": "Please provide a list of players visible in this photo with their jersey numbers."
},
{
"type": "image_url",
"image_url": {
"url": "https://ei.marketwatch.com/Multimedia/2019/02/15/Photos/ZH/MW-HE047_nbajer_20190215102153_ZH.jpg"
}
}
]},
],
response_format=Players,
)
Key components:
To enable structured output in MAX, simply include --enable-structured-output
.
To see other options, make sure to check out the help:
max serve --help
In this recipe, we've built a system for extracting structured data from images using Llama 3.2 Vision and MAX. We've explored:
This implementation provides a foundation for building more complex vision-based applications with structured output.
We're excited to see what you'll build with Llama 3.2 Vision and MAX! Share your projects and experiences with us using #ModularAI
on social media.
DETAILS
AUTHOR
Ehsan M. Kermani
AVAILABLE TASKS
pixi run server
pixi run main
PROBLEMS WITH THE CODE?
File an Issue
TAGS
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