Package org.springframework.ai.watsonx

Class WatsonxAiEmbeddingModel

java.lang.Object

org.springframework.ai.embedding.AbstractEmbeddingModel

org.springframework.ai.watsonx.WatsonxAiEmbeddingModel

All Implemented Interfaces:

EmbeddingModel, Model<EmbeddingRequest,EmbeddingResponse>

public class WatsonxAiEmbeddingModel
extends AbstractEmbeddingModel

EmbeddingModel implementation for Watsonx.ai.

Watsonx.ai allows developers to run large language models and generate embeddings. It supports open-source models available on Watsonx.ai models.

Please refer to the official Watsonx.ai website for the most up-to-date information on available models.

Since:

1.0.0

Author:

Pablo Sanchidrian Herrera

Field Summary

Fields inherited from class org.springframework.ai.embedding.AbstractEmbeddingModel

embeddingDimensions

Constructor Summary

Constructors

Constructor	Description
WatsonxAiEmbeddingModel(WatsonxAiApi watsonxAiApi)
WatsonxAiEmbeddingModel(WatsonxAiApi watsonxAiApi, WatsonxAiEmbeddingOptions defaultOptions)

Method Summary

Modifier and Type	Method	Description
EmbeddingResponse	call(EmbeddingRequest request)	Executes a method call to the AI model.
float[]	embed(Document document)	Embeds the given document's content into a vector.

Methods inherited from class org.springframework.ai.embedding.AbstractEmbeddingModel

dimensions, dimensions

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.springframework.ai.embedding.EmbeddingModel

embed, embed, embed, embedForResponse

Constructor Details

WatsonxAiEmbeddingModel

public WatsonxAiEmbeddingModel(WatsonxAiApi watsonxAiApi)

WatsonxAiEmbeddingModel

public WatsonxAiEmbeddingModel(WatsonxAiApi watsonxAiApi,
 WatsonxAiEmbeddingOptions defaultOptions)

Method Details

embed

public float[] embed(Document document)

Description copied from interface: EmbeddingModel

Embeds the given document's content into a vector.

Parameters:

document - the document to embed.

Returns:

the embedded vector.

call

public EmbeddingResponse call(EmbeddingRequest request)

Description copied from interface: Model

Executes a method call to the AI model.

Parameters:

request - the request object to be sent to the AI model

Returns:

the response from the AI model