HuggingFaceAPITextEmbedder

Embeds strings using Hugging Face APIs.

Basic Information

• Type: haystack_integrations.embedders.hugging_face_api_text_embedder.HuggingFaceAPITextEmbedder

Inputs

Parameter	Type	Default	Description
text	str		Text to embed.

Outputs

Parameter	Type	Default	Description
embedding	List[float]		A dictionary with the following keys: - embedding: The embedding of the input text.

Overview

Embeds strings using Hugging Face APIs.

Use it with the following Hugging Face APIs:

• Free Serverless Inference API
• Paid Inference Endpoints
• Self-hosted Text Embeddings Inference#### With paid inference endpoints

from haystack.components.embedders import HuggingFaceAPITextEmbedder
from haystack.utils import Secret
text_embedder = HuggingFaceAPITextEmbedder(api_type="inference_endpoints",
                                           api_params={"model": "BAAI/bge-small-en-v1.5"},
                                           token=Secret.from_token("<your-api-key>"))

print(text_embedder.run("I love pizza!"))

# {'embedding': [0.017020374536514282, -0.023255806416273117, ...],

With self-hosted text embeddings inference

from haystack.components.embedders import HuggingFaceAPITextEmbedder
from haystack.utils import Secret

text_embedder = HuggingFaceAPITextEmbedder(api_type="text_embeddings_inference",
                                           api_params={"url": "http://localhost:8080"})

print(text_embedder.run("I love pizza!"))

# {'embedding': [0.017020374536514282, -0.023255806416273117, ...],

Usage Example

components:
  HuggingFaceAPITextEmbedder:
    type: components.embedders.hugging_face_api_text_embedder.HuggingFaceAPITextEmbedder
    init_parameters:

Parameters

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
api_type	Union[HFEmbeddingAPIType, str]		The type of Hugging Face API to use.
api_params	Dict[str, str]		A dictionary with the following keys: - model: Hugging Face model ID. Required when api_type is SERVERLESS_INFERENCE_API. - url: URL of the inference endpoint. Required when api_type is INFERENCE_ENDPOINTS or TEXT_EMBEDDINGS_INFERENCE.
token	Optional[Secret]	Secret.from_env_var(['HF_API_TOKEN', 'HF_TOKEN'], strict=False)	The Hugging Face token to use as HTTP bearer authorization. Check your HF token in your account settings.
prefix	str		A string to add at the beginning of each text.
suffix	str		A string to add at the end of each text.
truncate	Optional[bool]	True	Truncates the input text to the maximum length supported by the model. Applicable when api_type is TEXT_EMBEDDINGS_INFERENCE, or INFERENCE_ENDPOINTS if the backend uses Text Embeddings Inference. If api_type is SERVERLESS_INFERENCE_API, this parameter is ignored.
normalize	Optional[bool]	False	Normalizes the embeddings to unit length. Applicable when api_type is TEXT_EMBEDDINGS_INFERENCE, or INFERENCE_ENDPOINTS if the backend uses Text Embeddings Inference. If api_type is SERVERLESS_INFERENCE_API, this parameter is ignored.

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		Text to embed.