// Vector API Implementation (Pinecone-like operations)
import { CBDAdapter } from '../cbd-adapter.js';
import { VectorQuery, VectorResult, CNDError } from '../types.js';

export class VectorAPI implements VectorQuery {
  constructor(
    private collection: string,
    private adapter: CBDAdapter
  ) { }

  async insert(
    id: string,
    vector: number[],
    metadata?: Record<string, any>
  ): Promise<void> {
    try {
      await this.adapter.storeVector(this.collection, id, vector, metadata || {});
    } catch (error) {
      throw new CNDError(
        `Vector insert failed: ${error}`,
        'VECTOR_INSERT_ERROR',
        { collection: this.collection, id, vectorDimension: vector.length }
      );
    }
  }

  async similarity(
    vector: number[],
    options?: { threshold?: number; limit?: number }
  ): Promise<VectorResult[]> {
    try {
      const searchOptions = {
        threshold: options?.threshold || 0.7,
        limit: options?.limit || 10
      };

      return await this.adapter.searchVectors(this.collection, vector, searchOptions);
    } catch (error) {
      throw new CNDError(
        `Vector similarity search failed: ${error}`,
        'VECTOR_SIMILARITY_ERROR',
        { collection: this.collection, vectorDimension: vector.length, options }
      );
    }
  }

  async delete(id: string): Promise<boolean> {
    try {
      // In real implementation, this would delete the vector from CBD Engine
      console.log(`Vector API: Deleting vector ${id} from ${this.collection}`);
      return true;
    } catch (error) {
      throw new CNDError(
        `Vector delete failed: ${error}`,
        'VECTOR_DELETE_ERROR',
        { collection: this.collection, id }
      );
    }
  }

  async update(
    id: string,
    vector: number[],
    metadata?: Record<string, any>
  ): Promise<void> {
    try {
      // In real implementation, this would update the vector in CBD Engine
      console.log(`Vector API: Updating vector ${id} in ${this.collection}`, {
        vectorDimension: vector.length,
        metadata
      });
    } catch (error) {
      throw new CNDError(
        `Vector update failed: ${error}`,
        'VECTOR_UPDATE_ERROR',
        { collection: this.collection, id, vectorDimension: vector.length }
      );
    }
  }

  // Advanced vector operations
  async upsert(
    id: string,
    vector: number[],
    metadata?: Record<string, any>
  ): Promise<void> {
    try {
      // Try to update first, then insert if not found
      await this.update(id, vector, metadata);
    } catch (error) {
      // If update fails, try insert
      await this.insert(id, vector, metadata);
    }
  }

  async fetch(ids: string[]): Promise<VectorResult[]> {
    try {
      // In real implementation, this would fetch vectors by IDs from CBD Engine
      console.log(`Vector API: Fetching vectors from ${this.collection}:`, ids);
      return [];
    } catch (error) {
      throw new CNDError(
        `Vector fetch failed: ${error}`,
        'VECTOR_FETCH_ERROR',
        { collection: this.collection, ids }
      );
    }
  }

  async query(
    vector: number[],
    options?: {
      topK?: number;
      filter?: Record<string, any>;
      includeMetadata?: boolean;
      includeValues?: boolean;
    }
  ): Promise<VectorResult[]> {
    try {
      const queryOptions = {
        threshold: 0,
        limit: options?.topK || 10,
        filter: options?.filter,
        includeMetadata: options?.includeMetadata !== false,
        includeValues: options?.includeValues || false
      };

      return await this.adapter.searchVectors(this.collection, vector, queryOptions);
    } catch (error) {
      throw new CNDError(
        `Vector query failed: ${error}`,
        'VECTOR_QUERY_ERROR',
        { collection: this.collection, vectorDimension: vector.length, options }
      );
    }
  }

  async describe(): Promise<{
    dimension: number;
    totalVectorCount: number;
    indexFullness: number;
  }> {
    try {
      // In real implementation, this would get collection stats from CBD Engine
      console.log(`Vector API: Describing collection ${this.collection}`);

      return {
        dimension: 1536, // Default OpenAI embedding dimension
        totalVectorCount: 0,
        indexFullness: 0
      };
    } catch (error) {
      throw new CNDError(
        `Vector describe failed: ${error}`,
        'VECTOR_DESCRIBE_ERROR',
        { collection: this.collection }
      );
    }
  }

  // Batch operations
  async insertBatch(vectors: Array<{
    id: string;
    vector: number[];
    metadata?: Record<string, any>;
  }>): Promise<void> {
    try {
      for (const { id, vector, metadata } of vectors) {
        await this.insert(id, vector, metadata);
      }
    } catch (error) {
      throw new CNDError(
        `Vector batch insert failed: ${error}`,
        'VECTOR_BATCH_INSERT_ERROR',
        { collection: this.collection, batchSize: vectors.length }
      );
    }
  }

  async deleteBatch(ids: string[]): Promise<number> {
    try {
      let deletedCount = 0;
      for (const id of ids) {
        const deleted = await this.delete(id);
        if (deleted) deletedCount++;
      }
      return deletedCount;
    } catch (error) {
      throw new CNDError(
        `Vector batch delete failed: ${error}`,
        'VECTOR_BATCH_DELETE_ERROR',
        { collection: this.collection, batchSize: ids.length }
      );
    }
  }

  // Semantic search helpers
  async semanticSearch(
    text: string,
    embedFunction: (text: string) => Promise<number[]>,
    options?: { limit?: number; threshold?: number }
  ): Promise<VectorResult[]> {
    try {
      const vector = await embedFunction(text);
      return this.similarity(vector, options);
    } catch (error) {
      throw new CNDError(
        `Semantic search failed: ${error}`,
        'VECTOR_SEMANTIC_SEARCH_ERROR',
        { collection: this.collection, text, options }
      );
    }
  }

  async hybridSearch(
    vector: number[],
    filters: Record<string, any>,
    options?: {
      vectorWeight?: number;
      filterWeight?: number;
      limit?: number;
    }
  ): Promise<VectorResult[]> {
    try {
      const searchOptions = {
        ...options,
        limit: options?.limit || 10,
        filter: filters,
        vectorWeight: options?.vectorWeight || 0.7,
        filterWeight: options?.filterWeight || 0.3
      };

      return await this.adapter.searchVectors(this.collection, vector, searchOptions);
    } catch (error) {
      throw new CNDError(
        `Hybrid search failed: ${error}`,
        'VECTOR_HYBRID_SEARCH_ERROR',
        { collection: this.collection, vectorDimension: vector.length, filters, options }
      );
    }
  }

  // Analytics and insights
  async getStats(): Promise<{
    totalVectors: number;
    averageScore: number;
    dimensions: number;
    lastUpdated: Date;
  }> {
    try {
      // In real implementation, this would get detailed stats from CBD Engine
      console.log(`Vector API: Getting stats for ${this.collection}`);

      return {
        totalVectors: 0,
        averageScore: 0,
        dimensions: 1536,
        lastUpdated: new Date()
      };
    } catch (error) {
      throw new CNDError(
        `Vector stats failed: ${error}`,
        'VECTOR_STATS_ERROR',
        { collection: this.collection }
      );
    }
  }

  async findSimilarClusters(
    vector: number[],
    clusterCount: number = 5
  ): Promise<Array<{ clusterId: string; similarity: number; vectors: VectorResult[] }>> {
    try {
      // In real implementation, this would use clustering algorithms in CBD Engine
      console.log(`Vector API: Finding similar clusters for ${this.collection}`, {
        vectorDimension: vector.length,
        clusterCount
      });

      return [];
    } catch (error) {
      throw new CNDError(
        `Vector clustering failed: ${error}`,
        'VECTOR_CLUSTERING_ERROR',
        { collection: this.collection, vectorDimension: vector.length, clusterCount }
      );
    }
  }
}