/**
 * This file was auto-generated by Fern from our API Definition.
 */
import * as CortexAI from "../../../../index.js";
/**
 * @example
 *     {
 *         tenant_id: "tenant_1234",
 *         question: "What is Cortex AI"
 *     }
 */
export interface QnASearchRequest {
    /** Unique identifier for the tenant/organization */
    tenant_id: string;
    /** Optional sub-tenant identifier used to organize data within a tenant. If omitted, the default sub-tenant created during tenant setup will be used. */
    sub_tenant_id?: string;
    /** The question to answer based on indexed sources */
    question: string;
    /** Maximum number of context chunks to retrieve */
    max_chunks?: number;
    /** Retrieval mode: 'fast' for single query, 'thinking' for multi-query with reranking */
    mode?: CortexAI.RetrieveMode;
    /** Hybrid search alpha (0.0 = sparse/keyword, 1.0 = dense/semantic) */
    alpha?: number;
    /** What to search: 'sources' for documents or 'memories' for user memories */
    search_mode?: CortexAI.SearchMode;
    /** Whether to include knowledge graph context for enhanced answers */
    include_graph_context?: boolean;
    /** Additional context to guide retrieval and answer generation */
    extra_context?: string;
    /** LLM provider for answer generation */
    llm_provider?: CortexAI.SupportedLlmProviders;
    /** Specific model to use (defaults to provider's default model) */
    model?: string;
    /** LLM temperature for answer generation (lower = more focused) */
    temperature?: number;
    /** Maximum tokens for the generated answer */
    max_tokens?: number;
}