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Showing content from https://django-mongodb-backend.readthedocs.io/en/latest/ref/models/indexes/ below:

Model index reference — Django MongoDB Backend 5.2.0b3.dev0 documentation

Some MongoDB-specific indexes, for use on a model’s Meta.indexes option, are available in django_mongodb_backend.indexes.

class SearchIndex(fields=(), name=None)¶

Added in version 5.2.0b0.

Creates a basic search index on the given field(s).

Some fields such as DecimalField aren’t supported. See the Atlas documentation for a complete list of unsupported data types.

If name isn’t provided, one will be generated automatically. If you need to reference the name in your search query and don’t provide your own name, you can lookup the generated one using Model._meta.indexes[0].name (substituting the name of your model as well as a different list index if your model has multiple indexes).

class VectorSearchIndex(*, fields=(), name=None, similarities)¶

Added in version 5.2.0b0.

A subclass of SearchIndex that creates a vector search index on the given field(s).

The index must reference at least one vector field: an ArrayField with a base_field of FloatField or IntegerField and a size. It cannot reference an ArrayField of any other type.

It may also have other fields to filter on, provided the field stores boolean, date, objectId, numeric, string, or uuid.

Available values for the required similarities keyword argument are "cosine", "dotProduct", and "euclidean" (see About the Similarity Functions for how to choose). You can provide this value either a string, in which case that value will be applied to all vector fields, or a list or tuple of values with a similarity corresponding to each vector field.

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