FastembedSparseTextEmbedder

FastembedSparseTextEmbedder computes string embedding using fastembed sparse models.

Basic Information

• Type: haystack_integrations.fastembed.src.haystack_integrations.components.embedders.fastembed.fastembed_sparse_text_embedder.FastembedSparseTextEmbedder

Inputs

Parameter	Type	Default	Description
text	str		A string to embed.

Outputs

Parameter	Type	Default	Description
sparse_embedding	SparseEmbedding		A dictionary with the following keys: - embedding: A list of floats representing the embedding of the input text.

Overview

Work in Progress

Bear with us while we're working on adding pipeline examples and most common components connections.

FastembedSparseTextEmbedder computes string embedding using fastembed sparse models.

Usage example:

from haystack_integrations.components.embedders.fastembed import FastembedSparseTextEmbedder

text = ("It clearly says online this will work on a Mac OS system. "
        "The disk comes and it does not, only Windows. Do Not order this if you have a Mac!!")

sparse_text_embedder = FastembedSparseTextEmbedder(
    model="prithivida/Splade_PP_en_v1"
)
sparse_text_embedder.warm_up()

sparse_embedding = sparse_text_embedder.run(text)["sparse_embedding"]

Usage Example

components:
  FastembedSparseTextEmbedder:
    type: fastembed.src.haystack_integrations.components.embedders.fastembed.fastembed_sparse_text_embedder.FastembedSparseTextEmbedder
    init_parameters:

Parameters

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
model	str	prithivida/Splade_PP_en_v1	Local path or name of the model in Fastembed's model hub, such as prithivida/Splade_PP_en_v1
cache_dir	Optional[str]	None	The path to the cache directory. Can be set using the FASTEMBED_CACHE_PATH env variable. Defaults to fastembed_cache in the system's temp directory.
threads	Optional[int]	None	The number of threads single onnxruntime session can use. Defaults to None.
progress_bar	bool	True	If True, displays progress bar during embedding.
parallel	Optional[int]	None	If > 1, data-parallel encoding will be used, recommended for offline encoding of large datasets. If 0, use all available cores. If None, don't use data-parallel processing, use default onnxruntime threading instead.
local_files_only	bool	False	If True, only use the model files in the cache_dir.
model_kwargs	Optional[Dict[str, Any]]	None	Dictionary containing model parameters such as k, b, avg_len, language.

Run Method Parameters

These are the parameters you can configure for the component's run() method. This means you can pass these parameters at query time through the API, in Playground, or when running a job. For details, see Modify Pipeline Parameters at Query Time.

Parameter	Type	Default	Description
text	str		A string to embed.