nemoguardrails.embeddings.providers.fastembed

Module Contents

Classes

Name	Description
`FastEmbedEmbeddingModel`	Embedding model using FastEmbed.

Functions

Name	Description
`get_executor`	-

API

class nemoguardrails.embeddings.providers.fastembed.FastEmbedEmbeddingModel(
    embedding_model: str,
    kwargs = {}
)

Bases: EmbeddingModel

Embedding model using FastEmbed.

This class represents an embedding model that utilizes the FastEmbed library for generating sentence embeddings.

Parameters:

embedding_model

str

The name or path of the pre-trained model.

embedding_size

= len(list(self.model.embed('test'))[0].tolist())

engine_name

= 'FastEmbed'

model

= Embedding(embedding_model, **kwargs)

nemoguardrails.embeddings.providers.fastembed.FastEmbedEmbeddingModel.encode(
    documents: typing.List[str]
) -> typing.List[typing.List[float]]

Encode a list of documents into their corresponding sentence embeddings.

Parameters:

documents

List[str]

The list of documents to be encoded.

Returns: List[List[float]]

List[List[float]]: The list of sentence embeddings, where each embedding is a list of floats.

nemoguardrails.embeddings.providers.fastembed.FastEmbedEmbeddingModel.encode_async(
    documents: typing.List[str]
) -> typing.List[typing.List[float]]

async

Encode a list of documents into their corresponding sentence embeddings.

Parameters:

documents

List[str]

The list of documents to be encoded.

Returns: List[List[float]]

List[List[float]]: The list of sentence embeddings, where each embedding is a list of floats.

nemoguardrails.embeddings.providers.fastembed.get_executor()