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Merge branch 'main' into Data-Masking-Config
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‎docs/release_notes.md‎

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### ✨ New Functionality
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-
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- [Orchestration] Added embedding generation support with new `OrchestrationClient#embed()` methods.
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- Added `OrchestrationEmbeddingModel` with `TEXT_EMBEDDING_3_SMALL`, `TEXT_EMBEDDING_3_LARGE`, `AMAZON_TITAN_EMBED_TEXT` and `NVIDIA_LLAMA_32_NV_EMBEDQA_1B` embedding models.
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- Introduced `OrchestrationEmbeddingRequest` for building requests fluently and `OrchestrationEmbeddingResponse#getEmbeddingVectors()` to retrieve embeddings.
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### 📈 Improvements
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-

‎orchestration/src/main/java/com/sap/ai/sdk/orchestration/OrchestrationClient.java‎

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}
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/**
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* Generate embeddings for the given request.
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* Generate embeddings for a {@code OrchestrationEmbeddingRequest} request.
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*
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* @param request the request containing the input text and other parameters.
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* @return the response containing the embeddings.
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* @throws OrchestrationClientException if the request fails
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* @since 1.9.0
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* @since 1.12.0
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*/
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@Nonnull
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EmbeddingsPostResponse embed(@Nonnull final EmbeddingsPostRequest request)
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public OrchestrationEmbeddingResponse embed(@Nonnull final OrchestrationEmbeddingRequest request)
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throws OrchestrationClientException {
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final var response = embed(request.createEmbeddingsPostRequest());
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return new OrchestrationEmbeddingResponse(response);
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}
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/**
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* Generates embeddings using the low-level API request.
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*
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* <p>This method provides direct access to the underlying API for advanced use cases. For most
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* scenarios, prefer {@link #embed(OrchestrationEmbeddingRequest)}.
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*
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* @param request the low-level API request
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* @return the low level response object
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* @throws OrchestrationClientException if the request fails
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* @since 1.12.0
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* @see #embed(OrchestrationEmbeddingRequest)
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*/
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@Nonnull
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public EmbeddingsPostResponse embed(@Nonnull final EmbeddingsPostRequest request)
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throws OrchestrationClientException {
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return executor.execute("/v2/embeddings", request, EmbeddingsPostResponse.class, customHeaders);
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}

‎orchestration/src/main/java/com/sap/ai/sdk/orchestration/OrchestrationEmbeddingModel.java‎

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package com.sap.ai.sdk.orchestration;
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import com.google.common.annotations.Beta;
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import com.sap.ai.sdk.core.AiModel;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsModelDetails;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsModelParams;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsModelParams.EncodingFormatEnum;
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import javax.annotation.Nonnull;
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import javax.annotation.Nullable;
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import lombok.AccessLevel;
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import lombok.AllArgsConstructor;
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import lombok.Value;
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import lombok.With;
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import lombok.experimental.Accessors;
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/**
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* Configuration for embedding models in the Orchestration service.
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*
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* @since 1.12.0
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*/
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@Beta
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@With
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@Value
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@Accessors(fluent = true)
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@AllArgsConstructor(access = AccessLevel.PRIVATE)
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public class OrchestrationEmbeddingModel implements AiModel {
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/** The name of the embedding model. */
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@Nonnull String name;
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/** The version of the model, defaults to latest if not specified. */
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@Nullable String version;
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/** The number of dimensions for the output embeddings. */
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@Nullable Integer dimensions;
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/** Whether to normalize the embedding vectors. */
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@Nullable Boolean normalize;
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/** Azure OpenAI Text Embedding 3 Small model */
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public static final OrchestrationEmbeddingModel TEXT_EMBEDDING_3_SMALL =
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new OrchestrationEmbeddingModel("text-embedding-3-small");
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/** Azure OpenAI Text Embedding 3 Large model */
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public static final OrchestrationEmbeddingModel TEXT_EMBEDDING_3_LARGE =
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new OrchestrationEmbeddingModel("text-embedding-3-large");
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/** Amazon Titan Embed Text model */
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public static final OrchestrationEmbeddingModel AMAZON_TITAN_EMBED_TEXT =
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new OrchestrationEmbeddingModel("amazon--titan-embed-text");
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/** NVIDIA LLaMA 3.2 7B NV EmbedQA model */
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public static final OrchestrationEmbeddingModel NVIDIA_LLAMA_32_NV_EMBEDQA_1B =
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new OrchestrationEmbeddingModel("nvidia--llama-3.2-nv-embedqa-1b");
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/**
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* Creates a new embedding model configuration with the specified name.
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*
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* @param name the model name
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*/
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public OrchestrationEmbeddingModel(@Nonnull final String name) {
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this(name, null, null, null);
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}
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@Nonnull
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EmbeddingsModelDetails createEmbeddingsModelDetails() {
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final var params =
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EmbeddingsModelParams.create()
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.dimensions(dimensions)
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.normalize(normalize)
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.encodingFormat(EncodingFormatEnum.FLOAT);
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return EmbeddingsModelDetails.create().name(name).version(version).params(params);
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}
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}

‎orchestration/src/main/java/com/sap/ai/sdk/orchestration/OrchestrationEmbeddingRequest.java‎

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package com.sap.ai.sdk.orchestration;
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import static lombok.AccessLevel.NONE;
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import static lombok.AccessLevel.PRIVATE;
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import com.google.common.annotations.Beta;
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import com.google.common.collect.Lists;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsInput;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsInputText;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsModelConfig;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsModuleConfigs;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsOrchestrationConfig;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsPostRequest;
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import com.sap.ai.sdk.orchestration.model.MaskingModuleConfigProviders;
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import java.util.List;
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import javax.annotation.Nonnull;
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import javax.annotation.Nullable;
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import lombok.AllArgsConstructor;
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import lombok.Getter;
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import lombok.Value;
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import lombok.With;
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import lombok.experimental.Tolerate;
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/**
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* Represents a request for generating embeddings through the SAP AI Core Orchestration service.
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*
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* @since 1.12.0
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*/
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@Beta
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@Value
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@AllArgsConstructor(access = PRIVATE)
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public class OrchestrationEmbeddingRequest {
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/** The embedding model to use for generating vector representations. */
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@Nonnull OrchestrationEmbeddingModel model;
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/** The list of text inputs to be converted into embeddings. */
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@Nonnull List<String> inputs;
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/** Optional masking providers for data privacy and security. */
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@With(value = PRIVATE)
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@Nullable
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List<MaskingProvider> masking;
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/** Optional embedding input type classification to optimize embedding generation. */
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@With(value = PRIVATE)
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@Getter(NONE)
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@Nullable
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EmbeddingsInput.TypeEnum inputType;
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/**
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* Create an embedding request using fluent API starting with model selection.
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*
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* <pre>{@code
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* OrchestrationEmbeddingRequest.forModel(myModel).forInputs("text to embed");
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* }</pre>
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*
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* @param model the embedding model to use
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* @return a step for specifying inputs
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*/
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@Nonnull
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public static InputStep forModel(@Nonnull final OrchestrationEmbeddingModel model) {
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return inputs -> new OrchestrationEmbeddingRequest(model, List.copyOf(inputs), null, null);
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}
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/** Builder step for specifying text inputs to embed. */
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@FunctionalInterface
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public interface InputStep {
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/**
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* Specifies text inputs to be embedded.
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*
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* @param inputs the text strings to embed
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* @return a new embedding request instance
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*/
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@Nonnull
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OrchestrationEmbeddingRequest forInputs(@Nonnull final List<String> inputs);
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/**
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* Specifies multiple text inputs using variable arguments.
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*
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* @param firstInput string to embed
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* @param inputs optional additional strings to embed
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* @return a new embedding request instance
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*/
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@Nonnull
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default OrchestrationEmbeddingRequest forInputs(
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@Nonnull final String firstInput, @Nonnull final String... inputs) {
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return forInputs(Lists.asList(firstInput, inputs));
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}
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}
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/**
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* Adds data masking providers to enable detection and masking of sensitive information.
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*
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* @param maskingProvider the primary masking provider
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* @param maskingProviders additional masking providers
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* @return a new request instance with the specified masking providers
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* @see MaskingProvider
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*/
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@Tolerate
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@Nonnull
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public OrchestrationEmbeddingRequest withMasking(
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@Nonnull final MaskingProvider maskingProvider,
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@Nonnull final MaskingProvider... maskingProviders) {
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return withMasking(Lists.asList(maskingProvider, maskingProviders));
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}
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/**
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* Configures this request to optimize embeddings for document content.
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*
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* @return a new request instance configured for document embedding
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*/
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@Nonnull
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public OrchestrationEmbeddingRequest asDocument() {
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return withInputType(EmbeddingsInput.TypeEnum.DOCUMENT);
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}
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/**
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* Configures this request to optimize embeddings for general text content.
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*
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* @return a new request instance configured for text embedding
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*/
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@Nonnull
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public OrchestrationEmbeddingRequest asText() {
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return withInputType(EmbeddingsInput.TypeEnum.TEXT);
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}
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/**
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* Configures this request to optimize embeddings for query content.
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*
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* @return a new request instance configured for query embedding
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*/
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@Nonnull
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public OrchestrationEmbeddingRequest asQuery() {
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return withInputType(EmbeddingsInput.TypeEnum.QUERY);
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}
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@Nonnull
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EmbeddingsPostRequest createEmbeddingsPostRequest() {
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final var input =
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EmbeddingsInput.create().text(EmbeddingsInputText.create(inputs)).type(inputType);
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final var embeddingsModelConfig =
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EmbeddingsModelConfig.create().model(model.createEmbeddingsModelDetails());
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final var modules =
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EmbeddingsOrchestrationConfig.create()
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.modules(EmbeddingsModuleConfigs.create().embeddings(embeddingsModelConfig));
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if (masking != null) {
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final var dpiConfigs = masking.stream().map(MaskingProvider::createConfig).toList();
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modules.getModules().setMasking(MaskingModuleConfigProviders.create().providers(dpiConfigs));
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}
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return EmbeddingsPostRequest.create().config(modules).input(input);
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}
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}

‎orchestration/src/main/java/com/sap/ai/sdk/orchestration/OrchestrationEmbeddingResponse.java‎

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package com.sap.ai.sdk.orchestration;
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import static lombok.AccessLevel.PACKAGE;
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import com.google.common.annotations.Beta;
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import com.sap.ai.sdk.orchestration.model.Embedding;
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import com.sap.ai.sdk.orchestration.model.EmbeddingsPostResponse;
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import java.util.ArrayList;
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import java.util.List;
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import javax.annotation.Nonnull;
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import lombok.AllArgsConstructor;
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import lombok.Value;
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/**
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* Response wrapper for orchestration embedding operations.
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*
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* <p>Wraps {@link EmbeddingsPostResponse} and provides convenient access to embedding vectors.
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*
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* @since 1.12.0
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*/
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@Beta
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@Value
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@AllArgsConstructor(access = PACKAGE)
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public class OrchestrationEmbeddingResponse {
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/** The original embedding response from the orchestration API. */
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@Nonnull EmbeddingsPostResponse originalResponse;
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/**
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* Extracts embedding vectors as float arrays.
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*
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* @return list of embedding vectors, never {@code null}
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*/
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@Nonnull
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public List<float[]> getEmbeddingVectors() {
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final var embeddings = new ArrayList<float[]>();
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for (final var container : originalResponse.getFinalResult().getData()) {
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final var bigDecimals = (Embedding.InnerBigDecimals) container.getEmbedding();
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final var values = bigDecimals.values();
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final float[] arr = new float[values.size()];
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for (int i = 0; i < values.size(); i++) {
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arr[i] = values.get(i).floatValue();
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}
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embeddings.add(arr);
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}
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return embeddings;
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}
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}

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