@rokmohar/medusa-plugin-meilisearch
Version:
Meilisearch plugin for Medusa 2
54 lines • 1.79 kB
TypeScript
import { Meilisearch } from 'meilisearch';
import { MeilisearchPluginOptions } from '../types';
/**
* MeiliSearch Embedder Service for AI-powered semantic search
* Handles vector search configuration and embedding management
*/
export declare class MeiliSearchEmbedder {
protected readonly config_: MeilisearchPluginOptions;
protected readonly client_: Meilisearch;
constructor(config: MeilisearchPluginOptions, client: Meilisearch);
/**
* Check if vector search is enabled and properly configured
*/
isVectorSearchEnabled(): boolean;
/**
* Configure embedders for an index based on vectorSearch configuration
*/
configureEmbedders(indexKey: string): Promise<void>;
/**
* Create embedder configuration based on provider settings
*/
private createEmbedderConfig;
/**
* Get default dimensions for common embedding models
*/
private getDefaultDimensions;
/**
* Create document template for embedding generation
*/
private createDocumentTemplate;
/**
* Enhance search options with vector search parameters
*/
enhanceSearchOptions(searchOptions: Record<string, unknown>, semanticSearch: boolean, semanticRatio: number): Record<string, unknown>;
/**
* Get embedder configuration status for admin panel
*/
getVectorSearchStatus(): {
enabled: boolean;
embeddingFields: never[];
semanticRatio: number;
provider?: undefined;
model?: undefined;
dimensions?: undefined;
} | {
enabled: boolean;
provider: "ollama" | "openai";
model: string;
dimensions: number;
embeddingFields: string[];
semanticRatio: number;
};
}
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