Package org.springframework.ai.oci

Class OCIEmbeddingModel

java.lang.Object

org.springframework.ai.embedding.AbstractEmbeddingModel

org.springframework.ai.oci.OCIEmbeddingModel

All Implemented Interfaces:

EmbeddingModel, Model<EmbeddingRequest,EmbeddingResponse>

public class OCIEmbeddingModel
extends AbstractEmbeddingModel

EmbeddingModel implementation that uses the OCI GenAI Embedding API.

Since:

1.0.0

Author:

Anders Swanson

Field Summary

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

embeddingDimensions

Constructor Summary

Constructors

Constructor	Description
OCIEmbeddingModel(com.oracle.bmc.generativeaiinference.GenerativeAiInference genAi, OCIEmbeddingOptions options)
OCIEmbeddingModel(com.oracle.bmc.generativeaiinference.GenerativeAiInference genAi, OCIEmbeddingOptions options, io.micrometer.observation.ObservationRegistry observationRegistry)

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

OCIEmbeddingModel

public OCIEmbeddingModel(com.oracle.bmc.generativeaiinference.GenerativeAiInference genAi,
 OCIEmbeddingOptions options)

OCIEmbeddingModel

public OCIEmbeddingModel(com.oracle.bmc.generativeaiinference.GenerativeAiInference genAi,
 OCIEmbeddingOptions options,
 io.micrometer.observation.ObservationRegistry observationRegistry)

Method Details

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

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.