import type { SqliteDatabase } from '../db/adapter.js';
export type EmbeddingMode = 'off' | 'optional' | 'required';
export type VectorBackendPreference = 'auto' | 'javascript' | 'sqlite-vec';
export type EmbeddingProviderKind = 'openai-compatible';
export type LocalEmbeddingProviderKind = 'local-transformers';
export interface EmbeddingConfig {
    readonly mode: EmbeddingMode;
    readonly provider: EmbeddingProviderKind;
    readonly baseUrl?: string;
    readonly model?: string;
    readonly dimensions?: number;
    readonly distanceCeiling?: number;
    readonly apiKey?: string;
    readonly allowRemote: boolean;
    readonly vectorBackend: VectorBackendPreference;
    readonly timeoutMs: number;
    readonly batchSize: number;
}
export interface EnabledEmbeddingConfig extends EmbeddingConfig {
    readonly mode: 'optional' | 'required';
    readonly baseUrl: string;
    readonly model: string;
    readonly dimensions: number;
    readonly distanceCeiling: number;
}
export interface EmbeddingProfileIdentity {
    readonly schemaVersion: 1;
    readonly providerKind: 'openai-compatible';
    readonly endpointFingerprint: string;
    readonly model: string;
    readonly dimensions: number;
    readonly distanceMetric: 'cosine';
    readonly documentTemplateVersion: 1;
    readonly queryTemplateVersion: 1;
    readonly distanceCeiling: number;
}
/** Immutable identity for a verified, local Transformers.js embedding space. */
export interface LocalEmbeddingProfileIdentity {
    readonly schemaVersion: 2;
    readonly providerKind: 'local-transformers';
    readonly presetId: 'local-small';
    readonly sourceModel: 'intfloat/multilingual-e5-small';
    readonly artifactRepository: 'Xenova/multilingual-e5-small';
    readonly modelRevision: string;
    readonly artifactManifestHash: string;
    readonly inferenceEngine: 'transformers-js';
    readonly inferenceEngineVersion: string;
    readonly dtype: 'q8';
    readonly pooling: 'mean';
    readonly normalize: true;
    readonly maximumTokens: 512;
    readonly dimensions: 384;
    readonly distanceMetric: 'cosine';
    readonly distanceCeiling: number;
    readonly inputContract: 'e5-query-passage-v1';
    readonly documentTemplateVersion: 2;
    readonly queryTemplateVersion: 2;
    readonly queryPrefix: 'query: ';
    readonly documentPrefix: 'passage: ';
}
export interface LocalEmbeddingProfile {
    readonly profileId: string;
    readonly identity: LocalEmbeddingProfileIdentity;
}
export interface EmbeddingProfile {
    readonly profileId: string;
    readonly identity: EmbeddingProfileIdentity | LocalEmbeddingProfileIdentity;
}
export interface PreparedSemanticQuery {
    readonly profileId: string;
    readonly dimensions: number;
    readonly vector: Float32Array;
    readonly vectorHash: string;
    readonly backendId: string;
    readonly distanceCeiling: number;
}
export interface EmbeddingDocument {
    readonly text: string;
    readonly bytes: Uint8Array;
    readonly documentHash: string;
    readonly truncated: boolean;
}
export interface VectorSearchInput {
    readonly profileId: string;
    readonly dimensions: number;
    readonly queryVector: Float32Array;
    readonly distanceCeiling: number;
    readonly workspace?: string;
    readonly excludedWorkspaces?: readonly string[];
    readonly limit: number;
}
export interface VectorHit {
    readonly entryId: string;
    readonly distance: number;
}
export interface VectorSearchBackend {
    readonly id: string;
    search(database: SqliteDatabase, input: VectorSearchInput): VectorHit[];
}
export interface EmbeddingProvider {
    readonly profile: EmbeddingProfileIdentity | LocalEmbeddingProfileIdentity;
    embed(inputs: readonly string[], options?: {
        signal?: AbortSignal;
    }): Promise<readonly Float32Array[]>;
}
export interface EmbeddingDrainResult {
    readonly claimed: number;
    readonly completed: number;
    readonly failed: number;
    readonly blocked: number;
    readonly remaining: number;
}
export interface EmbeddingRuntime {
    readonly mode: EmbeddingMode;
    readonly profileId: string | null;
    readonly backendId: string | null;
    readonly backend: VectorSearchBackend | null;
    prepareQuery(database: SqliteDatabase, text: string): Promise<PreparedSemanticQuery | null>;
    drain(options: {
        workspace?: string;
        maxJobs: number;
        deadlineMs: number;
    }): Promise<EmbeddingDrainResult>;
    close(): Promise<void>;
}
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