Django MariaDB Vector package on pypi - 'django-mariadb-vector'

📒 Django MariaDB Vector

pip install django-mariadb-vector

The Vector field, introduced in MariaDB 11.7, now has a simple library called 'django-mariadb-vector' that adds Django ORM support for it.

Created by me and shared for everyone to use.

🔸 pip install django-mariadb-vector

🔗 Repo: https://github.com/lexxai/django-mariadb-vector
🔗 Demo: https://github.com/lexxai/django-mariadb-vector-demo
🔗 Examples: https://github.com/lexxai/django-mariadb-vector-demo/tree/main/docs

MariaDB introduced native vector support, allowing you to store embeddings and perform similarity search directly in the database.

However, Django currently lacks:

• a native VECTOR model field
• ORM support for vector queries
• automatic migration
• support for vector indexes

 
This project fills that gap by providing a clean, Django-native way to work with MariaDB vectors.

Simple example of usage:

!pip install django-mariadb-vector

from django.db import models
from django_mariadb_vector import MariaDBVectorField, MariaDBVectorIndex, VecDistance


class MyModel(models.Model):
    embedding = MariaDBVectorField(dimensions=3)

    class Meta:
        indexes = [
            # Vector index (MariaDB 11.8.2+)
            MariaDBVectorIndex(fields=["embedding"], dimensions=3)
        ]

# Find 5 most similar records to a reference vector
reference_vector = [0.1, 0.2, 0.3]
results = MyModel.objects.annotate(
    distance=VecDistance("embedding", reference_vector)
).order_by("distance")[:5]
  

#Django #MairaDB #VectorDatabase #DjangoORM