FastembedTextEmbedder

FastembedTextEmbedder computes string embedding using fastembed embedding models.

Basic Information

• Type: haystack_integrations.fastembed.src.haystack_integrations.components.embedders.fastembed.fastembed_text_embedder.FastembedTextEmbedder

Inputs

Parameter	Type	Default	Description
text	str		A string to embed.

Outputs

Parameter	Type	Default	Description
embedding	List[float]		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.

FastembedTextEmbedder computes string embedding using fastembed embedding models.

Usage example:

from haystack_integrations.components.embedders.fastembed import FastembedTextEmbedder

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!!")

text_embedder = FastembedTextEmbedder(
    model="BAAI/bge-small-en-v1.5"
)
text_embedder.warm_up()

embedding = text_embedder.run(text)["embedding"]

Usage Example

components:
  FastembedTextEmbedder:
    type: fastembed.src.haystack_integrations.components.embedders.fastembed.fastembed_text_embedder.FastembedTextEmbedder
    init_parameters:

Parameters

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
model	str	BAAI/bge-small-en-v1.5	Local path or name of the model in Fastembed's model hub, such as BAAI/bge-small-en-v1.5
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.
prefix	str		A string to add to the beginning of each text.
suffix	str		A string to add to the end of each text.
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.

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.