import type { AuthContext } from '../auth/AuthContext';
import type { EmbeddingService } from '../../ai/service/EmbeddingService';
/**
 * 创建 Vector Store 请求
 */
export interface CreateVectorStoreRequest {
    /** 知识库名称 */
    name?: string;
    /** Container URL */
    url: string;
    /** Chunking 策略 */
    chunking_strategy?: 'auto' | 'static';
    /** 元数据 */
    metadata?: Record<string, string>;
}
/**
 * 修改 Vector Store 请求
 */
export interface ModifyVectorStoreRequest {
    name?: string;
    chunking_strategy?: 'auto' | 'static';
    metadata?: Record<string, string>;
}
/**
 * Vector Store 对象（OpenAI 兼容格式）
 */
export interface VectorStoreObject {
    id: string;
    object: 'vector_store';
    created_at: number;
    name: string;
    status: 'in_progress' | 'completed' | 'expired';
    usage_bytes: number;
    file_counts: {
        in_progress: number;
        completed: number;
        failed: number;
        cancelled: number;
        total: number;
    };
    last_active_at: number | null;
    metadata: Record<string, string>;
    url: string;
    chunking_strategy: string;
}
/**
 * Pod AI 配置
 */
export interface PodAIConfig {
    embeddingModel: string;
    migrationStatus: 'idle' | 'in_progress' | 'completed' | 'failed';
    previousModel?: string;
    migrationProgress?: number;
}
/**
 * 搜索请求
 */
export interface SearchRequest {
    query: string | string[];
    max_num_results?: number;
    filters?: Record<string, any>;
    ranking_options?: {
        ranker?: string;
        score_threshold?: number;
    };
    rewrite_query?: boolean;
}
/**
 * 搜索结果
 */
export interface SearchResult {
    file_id: string;
    file_url: string;
    filename: string;
    score: number;
    attributes: Record<string, any>;
    content: Array<{
        type: 'text';
        text: string;
    }>;
}
export interface VectorStoreServiceOptions {
    /** CSS base URL */
    cssBaseUrl: string;
    /** Token endpoint for login */
    tokenEndpoint: string;
    /** Embedding service */
    embeddingService: EmbeddingService;
    /** Webhook URL for receiving notifications (optional) */
    webhookUrl?: string;
}
/**
 * VectorStoreService - 知识库管理服务
 *
 * 提供 OpenAI 兼容的 Vector Store API
 */
export declare class VectorStoreService {
    private readonly logger;
    private readonly cssBaseUrl;
    private readonly tokenEndpoint;
    private readonly embeddingService;
    private readonly webhookUrl?;
    constructor(options: VectorStoreServiceOptions);
    /**
     * 创建 Vector Store（配置文件夹为知识库）
     */
    createVectorStore(request: CreateVectorStoreRequest, auth: AuthContext, accessToken?: string): Promise<VectorStoreObject>;
    /**
     * 列出所有 Vector Store
     */
    listVectorStores(auth: AuthContext, options?: {
        limit?: number;
        order?: 'asc' | 'desc';
        after?: string;
        before?: string;
    }): Promise<{
        object: 'list';
        data: VectorStoreObject[];
        has_more: boolean;
    }>;
    /**
     * 获取单个 Vector Store
     */
    getVectorStore(id: string, auth: AuthContext): Promise<VectorStoreObject>;
    /**
     * 修改 Vector Store
     */
    modifyVectorStore(id: string, request: ModifyVectorStoreRequest, auth: AuthContext): Promise<VectorStoreObject>;
    /**
     * 删除 Vector Store
     */
    deleteVectorStore(id: string, auth: AuthContext): Promise<{
        id: string;
        object: 'vector_store.deleted';
        deleted: boolean;
    }>;
    /**
     * 索引文件（由 webhook 调用）
     *
     * @param vectorStoreId Vector Store ID
     * @param fileUrl 文件 URL
     * @param auth 认证上下文
     * @param accessToken 访问令牌
     */
    indexFile(fileUrl: string, auth: AuthContext, accessToken: string): Promise<{
        id: string;
        status: string;
        vectorId: number;
    }>;
    /**
     * 获取文件应使用的分块策略（查找最近的父级 VectorStore）
     */
    private getChunkingStrategyForFile;
    /**
     * 删除文件索引（由 webhook 调用）
     */
    removeFileIndex(fileUrl: string, auth: AuthContext, accessToken: string): Promise<{
        deleted: boolean;
    }>;
    /**
     * 获取 Container 下的 file_counts 统计（基于 fileUrl 前缀匹配）
     */
    getFileCounts(containerUrl: string, auth: AuthContext): Promise<{
        in_progress: number;
        completed: number;
        failed: number;
        cancelled: number;
        total: number;
    }>;
    /**
     * 通过 vectorId 查找文件 URL（供 search 使用）
     * 注意：文件只索引一份，用 vectorId 即可查找
     */
    getFileUrlByVectorId(vectorId: number, auth: AuthContext): Promise<string | null>;
    /**
     * 根据 Container URL 查找 VectorStore
     */
    findVectorStoreByContainer(containerUrl: string, auth: AuthContext): Promise<VectorStoreObject | null>;
    /**
     * 根据文件 URL 查找所有匹配的 VectorStore（包括父级容器）
     *
     * 例如：文件 https://alice.pod/A/B/c.txt 会匹配：
     * - https://alice.pod/A/B/  (直接父级)
     * - https://alice.pod/A/    (祖先级)
     * - https://alice.pod/      (Pod 根)
     *
     * 这样文件可以被索引到多个知识库中
     */
    findVectorStoresByFileUrl(fileUrl: string, auth: AuthContext): Promise<VectorStoreObject[]>;
    /**
     * 搜索 Vector Store
     */
    search(vectorStoreId: string, request: SearchRequest, auth: AuthContext, accessToken: string): Promise<{
        object: 'vector_store.search_results.page';
        search_query: string;
        data: SearchResult[];
        has_more: boolean;
    }>;
    private generateId;
    /**
     * Hash subject + aspect 为向量 ID（供 webhook 索引使用）
     */
    hashSubjectAspect(subject: string, aspect: string): number;
    private extractContainerName;
    private extractFilename;
    private extractModelId;
    private modelResource;
    private getPodBaseUrl;
    private buildVectorStoreObject;
    private getPodDb;
    private getAiCredential;
    /**
     * 获取 Pod 级别的 AI 配置（全局 embedding model）
     */
    getAIConfig(auth: AuthContext): Promise<PodAIConfig | null>;
    /**
     * 设置全局 embedding model
     * 如果更换了模型，自动触发迁移（后台重新索引所有文件）
     */
    setEmbeddingModel(newModel: string, auth: AuthContext, accessToken: string): Promise<{
        success: boolean;
        migrationTriggered: boolean;
        message: string;
    }>;
    /**
     * 开始迁移：重新索引所有文件
     */
    private startMigration;
    /**
     * 获取资源内容（供 webhook 索引使用）
     */
    fetchResourceContent(url: string, accessToken: string): Promise<string>;
    private extractText;
    private extractTextFromTurtle;
    private extractTextFromJsonLd;
    private extractTextFromHtml;
    /**
     * Upsert 向量到 CSS（供 webhook 索引使用）
     */
    upsertVector(model: string, id: number, vector: number[], accessToken: string): Promise<void>;
    /**
     * 删除向量（供 webhook 索引使用）
     */
    deleteVector(model: string, id: number, accessToken: string): Promise<void>;
    private searchVectors;
    private unreadableVectorIdsForContainer;
    private canReadResource;
    /**
     * 订阅 Container 的变更通知（WebhookChannel2023）
     *
     * @param containerUrl Container URL
     * @param accessToken 访问令牌
     */
    private subscribeToContainer;
    /**
     * 发现 Solid Notification 端点
     *
     * 通过 HEAD 请求获取 Link header 中的 describedby，然后获取订阅端点
     */
    private discoverNotificationEndpoint;
    /**
     * 解析 Link header
     */
    private parseLinkHeader;
}