EmbeddingIndex#
EmbeddingIndex#
hsfs.embedding.EmbeddingIndex(index_name=None, features=None, col_prefix=None)
Represents an index for managing embeddings with associated features.
Arguments
- index_name
Optional[str]
: The name of the embedding index. - features
Optional[List[hsfs.embedding.EmbeddingFeature]]
: A list of EmbeddingFeature objects for the features that contain embeddings that should be indexed for similarity search. - col_prefix
Optional[str]
: The prefix to be added to column names.
Example
embedding_index = EmbeddingIndex()
embedding_index.add_embedding(name="user_vector", dimension=256)
embeddings = embedding_index.get_embeddings()
Methods#
add_embedding#
EmbeddingIndex.add_embedding(name, dimension, similarity_function_type="l2_norm")
Adds a new embedding feature to the index.
Example:
embedding_index = EmbeddingIndex()
embedding_index.add_embedding(name="user_vector", dimension=256)
Arguments
- name
str
: The name of the embedding feature. - dimension
int
: The dimensionality of the embedding feature. - similarity_function_type
Optional[hsfs.embedding.SimilarityFunctionType]
: The type of similarity function to be used.
from_json_response#
EmbeddingIndex.from_json_response(json_dict)
get_embeddings#
EmbeddingIndex.get_embeddings()
Returns the list of hsfs.embedding.EmbeddingFeature
objects associated with the index.
Returns
A list of hsfs.embedding.EmbeddingFeature
objects
json#
EmbeddingIndex.json()
to_dict#
EmbeddingIndex.to_dict()
{{embedding_feature}}