mongodb-rag-core/build/contentStore/MongoDbEmbeddedContentStore.d.ts

Common elements used by MongoDB Chatbot Framework components.

import { DatabaseConnection } from "../DatabaseConnection";
import { EmbeddedContentStore } from "./EmbeddedContent";
import { MakeMongoDbDatabaseConnectionParams } from "../MongoDbDatabaseConnection";
export type MakeMongoDbEmbeddedContentStoreParams = MakeMongoDbDatabaseConnectionParams & {
    /**
      The name of the collection in the database that stores {@link EmbeddedContent} documents.
      @default "embedded_content"
     */
    collectionName?: string;
    searchIndex: {
        /**
          Name of the search index to use for nearest-neighbor search.
          @default "vector_index"
         */
        name?: string;
        /**
          Embedding field name. Stored in the `EmbeddedContent.embeddings[embeddingName]` field.
         */
        embeddingName: string;
        /**
          Number of dimensions in the embedding field to index.
          Only used in index creation.
          @default 1536
         */
        numDimensions?: number;
        /**
          Atlas Vector Search filters to apply to the index creation.
          Only used in index creation.
          @default
          ```js
          [{ type: "filter", path: "sourceName" }]
          ```
         */
        filters?: {
            type: "filter";
            path: string;
        }[];
    };
};
export type MongoDbEmbeddedContentStore = EmbeddedContentStore & DatabaseConnection & {
    metadata: {
        databaseName: string;
        collectionName: string;
        embeddingPath: string;
        embeddingName: string;
    };
    init(): Promise<void>;
};
export declare function makeMongoDbEmbeddedContentStore({ connectionUri, databaseName, searchIndex: { embeddingName, numDimensions, filters, name, }, collectionName, }: MakeMongoDbEmbeddedContentStoreParams): MongoDbEmbeddedContentStore;
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