JinaTextEmbedder

A component for embedding strings using Jina AI models.

Basic Information

• Type: haystack_integrations.components.embedders.jina.text_embedder.JinaTextEmbedder

Inputs

Parameter	Type	Default	Description
text	str		The string to embed.

Outputs

Parameter	Type	Default	Description
embedding	List[float]		A dictionary with following keys: - embedding: The embedding of the input string. - meta: A dictionary with metadata including the model name and usage statistics.
meta	Dict[str, Any]		A dictionary with following keys: - embedding: The embedding of the input string. - meta: A dictionary with metadata including the model name and usage statistics.

Overview

Work in Progress

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

A component for embedding strings using Jina AI models.

Usage example:

from haystack_integrations.components.embedders.jina import JinaTextEmbedder

# Make sure that the environment variable JINA_API_KEY is set

text_embedder = JinaTextEmbedder(task="retrieval.query")

text_to_embed = "I love pizza!"

print(text_embedder.run(text_to_embed))

# {'embedding': [0.017020374536514282, -0.023255806416273117, ...],
# 'meta': {'model': 'jina-embeddings-v3',
#          'usage': {'prompt_tokens': 4, 'total_tokens': 4}}}

Usage Example

components:
  JinaTextEmbedder:
    type: jina.src.haystack_integrations.components.embedders.jina.text_embedder.JinaTextEmbedder
    init_parameters:

Parameters

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
api_key	Secret	Secret.from_env_var('JINA_API_KEY')	The Jina API key. It can be explicitly provided or automatically read from the environment variable JINA_API_KEY (recommended).
model	str	jina-embeddings-v3	The name of the Jina model to use. Check the list of available models on Jina documentation.
prefix	str		A string to add to the beginning of each text.
suffix	str		A string to add to the end of each text.
task	Optional[str]	None	The downstream task for which the embeddings will be used. The model will return the optimized embeddings for that task. Check the list of available tasks on Jina documentation.
dimensions	Optional[int]	None	Number of desired dimension. Smaller dimensions are easier to store and retrieve, with minimal performance impact thanks to MRL.
late_chunking	Optional[bool]	None	A boolean to enable or disable late chunking. Apply the late chunking technique to leverage the model's long-context capabilities for generating contextual chunk embeddings. The support of task and late_chunking parameters is only available for jina-embeddings-v3.

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		The string to embed.