@sap-ai-sdk/orchestration/dist/orchestration-types.d.ts

SAP Cloud SDK for AI is the official Software Development Kit (SDK) for **SAP AI Core**, **SAP Generative AI Hub**, and **Orchestration Service**.

import type { Xor } from '@sap-cloud-sdk/util';
import type { CustomRequestConfig } from '@sap-cloud-sdk/http-client';
import type { ChatModel, EmbeddingModel } from './model-types.js';
import type { ChatMessages, DataRepositoryType, DocumentGroundingFilter, DpiConfig, DpiEntities, FilteringStreamOptions, LlamaGuard38B, LLMModelDetails as OriginalLLMModelDetails, Template, TemplateRef, TemplatingChatMessage, DPIStandardEntity, DPICustomEntity, InputFilteringConfig, OutputFilteringConfig, MaskingProviderConfig, GlobalStreamOptions, ErrorResponse, AzureContentSafetyInputFilterConfig, AzureContentSafetyOutputFilterConfig, LlamaGuard38BFilterConfig, EmbeddingsModelDetails as OriginalEmbeddingsModelDetails, EmbeddingsModelParams as OriginalEmbeddingsModelParams, SAPDocumentTranslationInput, SAPDocumentTranslationOutput } from './client/api/schema/index.js';
/**
 * Chat completion request configuration.
 */
export interface ChatCompletionRequest {
    /**
     * Chat History.
     */
    messagesHistory?: ChatMessages;
    /**
     * New chat messages, including template messages.
     * @example
     * messages: [
     *   {
     *     role: 'system',
     *     content: 'You are a helpful assistant answering questions about {{product}}.'
     *   },
     *   {
     *     role: 'user',
     *     content: 'Can you give me an overview of its key benefits?'
     *   }
     * ]
     */
    messages?: ChatMessages;
    /**
     * Template parameters.
     * @example
     * placeholderValues: {
     *   product: 'SAP Cloud SDK'
     * }
     */
    placeholderValues?: Record<string, string>;
}
/**
 * LLM model details.
 */
export type LlmModelDetails = Omit<OriginalLLMModelDetails, 'name' | 'params'> & {
    name: ChatModel;
    params?: LlmModelParams;
};
/**
 * Prompt templating module configuration.
 */
export interface PromptTemplatingModule {
    /**
     * The prompt template to be used. Can be either a user defined template or a reference to a template in the prompt registry.
     */
    /**
     * Static prompts. Can be:
     * - A `template`: an array of templated chat messages (with {{?placeholders}}).
     * - An `id` or `scenario`, `name` and `version`: reference to a remote prompt template.
     *
     * This is meant for static instructions included with every call.
     * For per-request templating, use `messages` in `.chatCompletion()` instead.
     * @example
     * prompt: {
     *   template: [
     *     {
     *       role: 'system',
     *       content: 'You are an assistant for {{?product}}.'
     *     }
     *   ]
     * }
     */
    prompt?: Xor<PromptTemplate, TemplateRef> | string;
    /**
     * LLM model details.
     */
    model: LlmModelDetails;
}
/**
 * Representation of the `FilteringModuleConfig` schema.
 */
export interface FilteringModule {
    /**
     * List of provider type and filters.
     */
    input?: InputFilteringConfig;
    /**
     * List of provider type and filters.
     */
    output?: OutputFilteringConfig;
}
/**
 * Representation of the `MaskingModuleConfig` schema.
 */
export interface MaskingModule {
    /**
     * List of masking service providers
     * Min Items: 1.
     */
    masking_providers: MaskingProviderConfig[];
}
/**
 * Configuration for translation module.
 */
export interface TranslationModule {
    /**
     * Configuration for input translation.
     */
    input?: TranslationInputConfig;
    /**
     * Configuration for output translation.
     */
    output?: TranslationOutputConfig;
}
/**
 * Orchestration error response.
 */
export type OrchestrationErrorResponse = ErrorResponse;
/**
 * Model Parameters for LLM module configuration.
 */
export type LlmModelParams = {
    max_tokens?: number;
    temperature?: number;
    frequency_penalty?: number;
    presence_penalty?: number;
    top_p?: number;
    n?: number;
} & Record<string, any>;
/**
 * Representation of the 'Template' schema.
 */
export type PromptTemplate = Omit<Template, 'template'> & {
    /**
     * A chat message array to be formatted with values from `placeholderValues`.
     * Both `role` and `content` can use {{?variable}} placeholders.
     *
     * For dynamic templating (changing per request), pass templated messages directly in `.chatCompletion({ messages })`.
     * @example
     * // Static template: passed once in client config
     * templating: {
     *   template: [
     *     {
     *       role: 'system',
     *       content: 'You are a helpful assistant for {{?product}}.'
     *     }
     *   ]
     * }
     */
    template?: TemplatingChatMessage;
};
/**
 * Orchestration module configuration.
 */
export interface OrchestrationModuleConfig {
    /**
     * Prompt templating configuration.
     */
    promptTemplating: PromptTemplatingModule;
    /**
     * Filtering module configuration for both input and output filters.
     * To configure a filter, use convenience functions like `buildAzureContentSafetyFilter`, `buildLlamaGuard38BFilter`, etc..
     * @example
     * filtering: {
     *   input: {
     *     filters: [
     *       buildAzureContentSafetyFilter('input', { hate: 'ALLOW_SAFE', violence: 'ALLOW_SAFE_LOW_MEDIUM' })
     *     ]
     *   }
     * }
     */
    filtering?: FilteringModule;
    /**
     * Masking module configuration.
     */
    masking?: MaskingModule;
    /**
     * Grounding module configuraton.
     */
    grounding?: GroundingModule;
    /**
     * Translation module configuration.
     */
    translation?: TranslationModule;
}
/**
 * Request options for orchestration.
 */
export interface RequestOptions {
    /**
     * Prompt configuration.
     */
    request?: ChatCompletionRequest;
    /**
     * Custom request configuration.
     */
    requestConfig?: CustomRequestConfig;
    /**
     * Whether to stream the response.
     */
    stream?: boolean;
    /**
     * Options for the stream.
     */
    streamOptions?: StreamOptions;
}
/**
 * Options for the stream.
 */
export interface StreamOptions {
    /**
     * LLM specific stream options.
     */
    promptTemplating?: {
        include_usage?: boolean;
        [key: string]: any;
    } | null;
    /**
     * Output filtering stream options.
     */
    outputFiltering?: FilteringStreamOptions;
    /**
     * Global stream options.
     */
    global?: GlobalStreamOptions;
}
/**
 * Representation of the `GroundingModuleConfig` schema.
 */
export interface GroundingModule {
    /**
     * @example 'document_grounding_service'
     */
    type: 'document_grounding_service' | any;
    /**
     * Grounding service configuration.
     */
    config: {
        /**
         * Document grounding service filters to be used.
         */
        filters?: DocumentGroundingFilter[];
        /**
         * Placeholders to be used for grounding input questions and output.
         */
        placeholders: {
            /**
             * Contains the input parameters used for grounding input questions
             * Min Items: 1.
             */
            input: string[];
            /**
             * Placeholder name for grounding output.
             * @example 'groundingOutput'
             */
            output: string;
        };
        /**
         * Parameter name used for specifying metadata parameters.
         */
        metadata_params?: string[];
    };
}
/**
 * Represents a filter configuration for the Document Grounding Service.
 */
export type DocumentGroundingServiceFilter = Omit<DocumentGroundingFilter, 'data_repository_type'> & {
    /**
     * Defines the type of data repository.
     * If not set, the default value is 'vector'.
     */
    data_repository_type?: DataRepositoryType;
};
/**
 * Represents the configuration for the Document Grounding Service.
 */
export interface DocumentGroundingServiceConfig {
    /**
     * Document grounding service filters to be used.
     */
    filters?: DocumentGroundingServiceFilter[];
    /**
     * Placeholders to be used for grounding input questions and output.
     */
    placeholders: {
        /**
         * Contains the input parameters used for grounding input questions
         * Min Items: 1.
         */
        input: string[];
        /**
         * Placeholder name for grounding output.
         * @example "groundingOutput"
         */
        output: string;
    };
    /**
     * Parameter name used for specifying metadata parameters.
     */
    metadata_params?: string[];
}
/**
 * Defines the type of the DPI masking entity.
 */
type DpiEntity = DpiEntities | DPIStandardEntity | (DPICustomEntity & {
    type: 'custom';
});
/**
 * Represents the configuration for the masking provider SAP Data Privacy Integration.
 */
export type DpiMaskingConfig = Omit<DpiConfig, 'type' | 'entities' | 'mask_grounding_input'> & {
    entities: [DpiEntity, ...DpiEntity[]];
    mask_grounding_input?: boolean;
};
interface AzureContentSafetyFilterBaseParameters {
    /**
     * The filter category for hate content.
     */
    hate?: AzureFilterThreshold;
    /**
     * The filter category for self-harm content.
     */
    self_harm?: AzureFilterThreshold;
    /**
     * The filter category for sexual content.
     */
    sexual?: AzureFilterThreshold;
    /**
     * The filter category for violence content.
     */
    violence?: AzureFilterThreshold;
}
/**
 * Output Parameters for Azure content safety output filter.
 */
export interface AzureContentSafetyFilterOutputParameters extends AzureContentSafetyFilterBaseParameters {
    /**
     * Detect protected code content from known GitHub repositories. The scan includes software libraries, source code, algorithms, and other proprietary programming content.
     */
    protected_material_code?: boolean;
}
/**
 * Input parameters for Azure content safety input filter.
 */
export interface AzureContentSafetyFilterInputParameters extends AzureContentSafetyFilterBaseParameters {
    /**
     * A flag to use prompt shield.
     */
    prompt_shield?: boolean;
}
/**
 * A descriptive constant for Azure content safety filter threshold.
 * @internal
 */
export declare const supportedAzureFilterThresholds: {
    readonly ALLOW_SAFE: 0;
    readonly ALLOW_SAFE_LOW: 2;
    readonly ALLOW_SAFE_LOW_MEDIUM: 4;
    readonly ALLOW_ALL: 6;
};
/**
 * The Azure threshold level supported for each azure content filter category.
 */
export type AzureFilterThreshold = keyof typeof supportedAzureFilterThresholds;
/**
 * The filter categories supported for Llama Guard 3 8B filter.
 */
export type LlamaGuard38BCategory = keyof LlamaGuard38B;
/**
 * Type for module configurations (input or output).
 * @internal
 */
export type ConfigType = 'input' | 'output';
/**
 * Category for translation application scope.
 */
export type TranslationApplyToCategory = 'placeholders' | 'template_roles';
/**
 * Configuration selector for applying translation to specific placeholders or message roles.
 */
export interface DocumentTranslationApplyToSelector {
    /**
     * Category to apply translation to.
     */
    category: TranslationApplyToCategory;
    /**
     * List of placeholders or roles to apply translation to.
     * @example [
     *   "groundingInput",
     *   "inputContext"
     * ]
     */
    items: string[];
    /**
     * Language of the text to be translated.
     * @example "de-DE"
     */
    sourceLanguage?: string;
}
/**
 * Target language for translation, either a language code or a selector configuration.
 */
export type TranslationTargetLanguage = string | DocumentTranslationApplyToSelector;
/**
 * Input parameters for translation configuration.
 */
interface TranslationConfigParametersInput {
    /**
     * Language of the text to be translated.
     * @example sourceLanguage: 'de-DE'
     */
    sourceLanguage?: string;
    /**
     * Language to which the text should be translated.
     * @example targetLanguage: 'en-US'
     */
    targetLanguage: string;
    /**
     * If true, the messages history will be translated as well.
     * @default true
     */
    translateMessagesHistory?: boolean;
    /**
     * Configuration for applying translation to specific placeholders or message roles.
     * @example applyTo: [{ category: 'placeholders', items: ['user_input'], sourceLanguage: 'de-DE' }]
     */
    applyTo?: DocumentTranslationApplyToSelector[];
}
/**
 * Output parameters for translation configuration.
 */
interface TranslationConfigParametersOutput {
    /**
     * Language of the text to be translated.
     * @example sourceLanguage: 'de-DE'
     */
    sourceLanguage?: string;
    /**
     * Language to which the text should be translated.
     * @example targetLanguage: 'en-US'
     */
    targetLanguage: TranslationTargetLanguage;
}
/**
 * Output parameters for translation output configuration.
 */
export type TranslationOutputParameters = TranslationConfigParametersOutput;
/**
 * Input parameters for translation input configuration.
 */
export type TranslationInputParameters = TranslationConfigParametersInput;
/**
 * Parameters for translation configurations.
 */
export type TranslationConfigParams<T extends ConfigType> = T extends 'input' ? TranslationInputParameters : TranslationOutputParameters;
/**
 * Input configuration for translation module.
 */
export type TranslationInputConfig = SAPDocumentTranslationInput;
/**
 * Output configuration for translation module.
 */
export type TranslationOutputConfig = SAPDocumentTranslationOutput;
/**
 * Return type for translation configurations.
 */
export type TranslationReturnType<T extends ConfigType> = T extends 'input' ? TranslationInputConfig : TranslationOutputConfig;
/**
 * Parameters for Azure content safety filters.
 */
export type AzureContentSafetyFilterParameters<T extends ConfigType> = T extends 'input' ? AzureContentSafetyFilterInputParameters : AzureContentSafetyFilterOutputParameters;
/**
 * Filter return type for Azure Content Safety.
 */
export type AzureContentSafetyFilterReturnType<T extends ConfigType> = T extends 'input' ? AzureContentSafetyInputFilterConfig : AzureContentSafetyOutputFilterConfig;
/**
 * Input filter configuration for Llama Guard 3 8B.
 */
export type LlamaGuard38BInputFilterConfig = LlamaGuard38BFilterConfig;
/**
 * Output filter configuration for Llama Guard 3 8B.
 */
export type LlamaGuard38BOutputFilterConfig = LlamaGuard38BFilterConfig;
/**
 * Filter return type for Llama Guard 3 8B.
 */
export type LlamaGuard38BFilterReturnType<T extends ConfigType> = T extends 'input' ? LlamaGuard38BInputFilterConfig : LlamaGuard38BOutputFilterConfig;
/**
 * Representation of the 'DpiConfig' schema.
 */
export type DpiMaskingProviderConfig = DpiConfig;
/**
 * Embedding request configuration.
 */
export interface EmbeddingRequest {
    /**
     * Text input for which embeddings need to be generated.
     * Can be a single string or array of strings.
     * @example
     * input: "This is a text to embed" or
     * input: ["Text 1", "Text 2", "Text 3"]
     */
    input: string | string[];
    /**
     * Represents the task for which the embeddings need to be generated.
     * @default 'text'
     */
    type?: 'text' | 'document' | 'query';
}
/**
 * Embedding model details.
 */
export type EmbeddingModelDetails = Omit<OriginalEmbeddingsModelDetails, 'name' | 'params'> & {
    name: EmbeddingModel;
    params?: EmbeddingModelParams;
};
/**
 * Embedding model parameters.
 */
export type EmbeddingModelParams = OriginalEmbeddingsModelParams;
/**
 * Embedding model configuration.
 */
export interface EmbeddingModelConfig {
    /**
     * Model details for embedding generation.
     */
    model: EmbeddingModelDetails;
}
/**
 * Embedding module configuration.
 */
export interface EmbeddingModuleConfig {
    /**
     * Embeddings model configuration.
     */
    embeddings: EmbeddingModelConfig;
    /**
     * Masking module configuration.
     */
    masking?: MaskingModule;
}
/**
 * Embedding data with vector and index information.
 */
export interface EmbeddingData {
    /**
     * The object type, which is always "embedding".
     */
    object: 'embedding';
    /**
     * The embedding vector, either as a number array or base64-encoded string.
     */
    embedding: number[] | string;
    /**
     * The index of the embedding in the list of embeddings.
     */
    index: number;
}
export {};
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