@sap-ai-sdk/langchain/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 { OrchestrationModuleConfig as OrchestrationModuleConfigWithStringTemplating, PromptTemplate, PromptTemplatingModule, StreamOptions } from '@sap-ai-sdk/orchestration';
import type { CacheControl, ChatCompletionTool, ResponseFormatJsonObject, ResponseFormatJsonSchema, ResponseFormatText, TemplateRef } from '@sap-ai-sdk/orchestration/internal.js';
import type { Xor } from '@sap-cloud-sdk/util';
import type { BaseChatModelCallOptions, BaseChatModelParams, BindToolsInput } from '@langchain/core/language_models/chat_models';
import type { CustomRequestConfig } from '@sap-ai-sdk/core';
/**
 * Tool type for LangChain Orchestration client.
 */
export type ChatOrchestrationToolType = ChatCompletionTool | BindToolsInput;
/**
 * Langchain parameters for {@link OrchestrationClient} constructor `langchainOptions` argument.
 */
export type LangChainOrchestrationChatModelParams = BaseChatModelParams & {
    /**
     * Whether the model should automatically stream responses when using `invoke()`.
     * If {@link disableStreaming} is set to `true`, this option will be ignored.
     * If {@link streaming} is explicitly set to `false`, {@link disableStreaming} will be set to `true`.
     */
    streaming?: boolean;
};
/**
 * Options for an orchestration call.
 */
export type OrchestrationCallOptions = Pick<BaseChatModelCallOptions, 'stop' | 'signal' | 'timeout' | 'callbacks' | 'metadata' | 'runId' | 'runName' | 'tags' | 'ls_structured_output_format'> & {
    customRequestConfig?: CustomRequestConfig;
    strict?: boolean;
    tools?: ChatOrchestrationToolType[];
    promptIndex?: number;
    placeholderValues?: Record<string, string>;
    streamOptions?: StreamOptions;
    responseFormat?: ResponseFormatText | ResponseFormatJsonObject | ResponseFormatJsonSchema;
    /**
     * Cache control configuration for prompt caching. When provided, a cache
     * breakpoint is automatically applied to the last cacheable text block of
     * the last message so the breakpoint advances naturally as the conversation
     * grows. This removes the need to place `cache_control` on individual
     * content blocks manually.
     *
     * Only applies to models that support `cache_control` through orchestration
     * (Anthropic Claude and Amazon Nova model families). Other models will
     * ignore the directive. See the
     * {@link https://help.sap.com/docs/sap-ai-core/generative-ai/prompt-caching | SAP AI Core prompt caching docs}
     * for supported models and breakpoint limits.
     */
    cache_control?: CacheControl;
};
/**
 * Orchestration module configuration for LangChain.
 */
export type LangChainOrchestrationModuleConfig = Omit<OrchestrationModuleConfigWithStringTemplating, 'promptTemplating'> & {
    promptTemplating: Omit<PromptTemplatingModule, 'prompt'> & {
        prompt?: Xor<PromptTemplate, TemplateRef>;
    };
};
/**
 * Non-empty list of orchestration module configurations for module fallback.
 * The orchestration service will try each configuration in order until one succeeds.
 * @example
 * const fallbackConfig: OrchestrationModuleConfigList = [
 *   {
 *     promptTemplating: {
 *       model: { name: 'gpt-5.4', timeout: 5 }
 *     }
 *   },
 *   {
 *     promptTemplating: {
 *       model: { name: 'gpt-5.4-nano' }
 *     }
 *   }
 * ];
 */
export type LangChainOrchestrationModuleConfigList = [
    LangChainOrchestrationModuleConfig,
    ...LangChainOrchestrationModuleConfig[]
];
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