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FastEmbedEncoder Objects

class FastEmbedEncoder(DenseEncoder)

Dense encoder that uses local FastEmbed to embed documents. Supports text only.

Requires the fastembed package which can be installed with pip install 'semantic-router[fastembed]'

Arguments:

  • name: The name of the embedding model to use.
  • max_length: The maximum length of the input text.
  • cache_dir: The directory to cache the embedding model.
  • threads: The number of threads to use for the embedding.

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__init__

def __init__(score_threshold: float = 0.5, **data)

Initialize the FastEmbed encoder.

Arguments:

  • score_threshold (float): The threshold for the score of the embedding.

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__call__

def __call__(docs: List[str]) -> List[List[float]]

Embed a list of documents. Supports text only.

Arguments:

  • docs (List[str]): The documents to embed.

Raises:

  • ValueError: If the embedding fails.

Returns:

List[List[float]]: The vector embeddings of the documents.

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