# Django Client for Lantern
## Install
```sh
pip install lantern-django
```
## Basic usage
Create a migration to enable the extensions:
```python
from django.db import migrations
from lantern_django import LanternExtension, LanternExtrasExtension
class Migration(migrations.Migration):
operations = [
LanternExtension(),
LanternExtrasExtension(),
]
```
Add a `REAL[]` field to your model
```python
from django.db import models
from django.contrib.postgres.fields import ArrayField
from lantern_django import RealField
class Item(models.Model):
embedding = ArrayField(RealField(), size=3, null=True)
```
Insert a vector
```python
item = Item(embedding=[1, 2, 3])
item.save()
```
Get the nearest neighbors to a vector
```python
from lantern_django import L2Distance
Item.objects.order_by(L2Distance('embedding', [3, 1, 2]))[:5]
```
Get nearest neighbors to a text embedding
```python
distance = L2Distance('embedding', TextEmbedding(
'BAAI/bge-small-en', 'hello'))
results = Item.objects.annotate(distance=distance).order_by('distance')[:5]
```
Get the distance
```python
Item.objects.annotate(distance=L2Distance('embedding', [3, 1, 2]))
```
Get items within a certain distance
```python
Item.objects.alias(distance=L2Distance('embedding', [3, 1, 2])).filter(distance__lt=5)
```
Add an index
```python
from lantern_django import HnswIndex
class Item(models.Model):
class Meta:
indexes = [
HnswIndex(
name='hnsw_idx',
fields=['embedding'],
m=16,
ef=64,
ef_construction=64,
dim=384,
opclasses=['dist_l2sq_ops']
)
]
```
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