import type { EmbeddingService } from '../../ai/service';
import type { RdfEngineLike, RdfTextChunkInput, RdfTextSourceInput, RdfVectorSourceInput } from '../../storage/rdf/types';
import type { StoreContext } from '../chatkit/store';
import { type EmbeddingProviderFailureCategory } from '../../ai/service/EmbeddingProviderError';
export type RdfVectorIndexingSkippedReason = 'rdf_engine_unavailable' | 'vector_index_unavailable' | 'ai_config_unavailable' | 'embedding_model_unavailable' | 'text_source_unavailable' | EmbeddingProviderFailureCategory;
export interface RdfSearchIndexingServiceOptions {
    rdfEngine?: Pick<RdfEngineLike, 'indexVectorSource' | 'deleteVectorSource' | 'listTextSourceChunks'>;
    store: {
        getAiConfig(context: StoreContext): Promise<RdfSearchAiConfig | undefined> | RdfSearchAiConfig | undefined;
    };
    embeddingService: Pick<EmbeddingService, 'embedBatch'>;
    maxChunks?: number;
    maxEmbeddingInputChars?: number;
    embeddingInputKinds?: RdfEmbeddingInputKind[];
    projectionPolicyVersion?: string;
    summaryService?: RdfEmbeddingSummaryService;
    summaryPromptVersion?: string;
}
export interface RdfSearchAiConfig {
    providerId: string;
    baseUrl: string;
    proxyUrl?: string;
    defaultModel?: string;
    embeddingModel?: string;
    embeddingModelVersion?: string;
    apiKey: string;
    credentialId: string;
}
export interface IndexRdfVectorSourceInput {
    context?: StoreContext;
    embeddingConfig?: RdfSearchAiConfig;
    source: RdfTextSourceInput & RdfVectorSourceInput;
    text?: string;
    chunks?: RdfTextChunkInput[];
}
export interface DeleteRdfVectorSourceInput {
    source: string;
}
export interface RebuildRdfVectorSourceInput {
    context?: StoreContext;
    embeddingConfig?: RdfSearchAiConfig;
    sourceKey: string;
}
export type RdfVectorIndexingResult = {
    status: 'indexed';
    source: string;
    sourceHash?: string;
    sourceVersion?: string;
    providerId?: string;
    model?: string;
    modelVersion?: string;
    configFingerprint?: string;
    chunkCount: number;
    skippedInputs?: RdfSkippedEmbeddingInput[];
    summarizedInputs?: RdfSummarizedEmbeddingInput[];
} | {
    status: 'skipped';
    source: string;
    sourceHash?: string;
    sourceVersion?: string;
    reason: RdfVectorIndexingSkippedReason;
    providerId?: string;
    model?: string;
    modelVersion?: string;
    configFingerprint?: string;
    message?: string;
} | {
    status: 'retryable';
    source: string;
    sourceHash?: string;
    sourceVersion?: string;
    reason: EmbeddingProviderFailureCategory;
    providerId: string;
    model: string;
    modelVersion?: string;
    configFingerprint: string;
    message?: string;
};
export interface RdfVectorDeleteResult {
    status: 'deleted' | 'skipped';
    source: string;
    deletedChunks: number;
    reason?: 'rdf_engine_unavailable' | 'vector_index_unavailable';
}
export type RdfEmbeddingInputKind = 'locator' | 'semantic';
export interface RdfSkippedEmbeddingInput {
    chunkKey: string;
    inputKind: RdfEmbeddingInputKind;
    reason: 'input_too_large' | 'summary_failed' | 'summary_too_large';
    inputChars: number;
    maxChars: number;
    summaryChars?: number;
    message?: string;
}
export interface RdfEmbeddingSummaryRequest {
    content: string;
    inputKind: RdfEmbeddingInputKind;
    chunkKey: string;
    sourceHash?: string;
    maxChars: number;
    promptVersion: string;
}
export interface RdfEmbeddingSummaryResult {
    content: string;
    provider: string;
    model: string;
    promptVersion?: string;
    rounds?: number;
}
export interface RdfEmbeddingSummaryService {
    summarize(request: RdfEmbeddingSummaryRequest): Promise<RdfEmbeddingSummaryResult> | RdfEmbeddingSummaryResult;
}
export interface RdfSummarizedEmbeddingInput {
    chunkKey: string;
    inputKind: RdfEmbeddingInputKind;
    originalChars: number;
    summaryChars: number;
    rounds: number;
}
export declare const DEFAULT_RDF_VECTOR_MODEL_VERSION = "unversioned";
export declare const DEFAULT_RDF_VECTOR_PROJECTION_POLICY_VERSION = "rdf-vector-projection-v1";
export declare function normalizeRdfVectorModelVersion(value: string | undefined): string;
/**
 * Product-level bridge from Pod-owned AI credentials to the RDF vector index.
 *
 * CSS storage writes can keep text search sources current because they already
 * have the resource bytes. Vector writes need user Pod AI credentials, so they
 * live here at the product/service boundary instead of inside MixDataAccessor.
 */
export declare class RdfSearchIndexingService {
    private readonly options;
    constructor(options: RdfSearchIndexingServiceOptions);
    rebuildVectorSource(input: RebuildRdfVectorSourceInput): Promise<RdfVectorIndexingResult>;
    indexVectorSource(input: IndexRdfVectorSourceInput): Promise<RdfVectorIndexingResult>;
    deleteVectorSource(input: DeleteRdfVectorSourceInput): Promise<RdfVectorDeleteResult>;
    private sourceWithHash;
    private textChunks;
    private embeddingInputs;
    private embeddingInputKinds;
    private projectionPolicyVersion;
    private embeddingInputContent;
    private resolveEmbeddingInputBudget;
    private summarizeEmbeddingInput;
    private skippedEmbeddingInput;
    private indexedResult;
    private skippedResult;
}