langchain.js
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    interface IndexConfig {
        createAllMetricIndexes?: boolean;
        dims: number;
        distanceMetric?: DistanceMetric;
        embed: Embeddings | EmbeddingsFunc;
        fields?: string[];
        hnsw?: HNSWConfig;
        indexType?: VectorIndexType;
        ivfflat?: IVFFlatConfig;
    }
    Index

    Properties

    createAllMetricIndexes?: boolean

    Whether to create indexes for all distance metrics. If false, only creates index for the specified distanceMetric.

    false
    
    dims: number

    Number of dimensions in the embedding vectors.

    distanceMetric?: DistanceMetric

    Distance metric for vector similarity.

    'cosine'
    

    Embedding function to generate embeddings from text. Can be a LangChain Embeddings instance or a function.

    fields?: string[]

    Fields to extract text from for embedding generation. Uses JSON path syntax. Defaults to ["$"] (entire document).

    hnsw?: HNSWConfig

    HNSW-specific configuration parameters. Only used when indexType is 'hnsw'.

    indexType?: VectorIndexType

    Vector index type to use.

    • 'hnsw': Hierarchical Navigable Small World (best for most use cases)
    • 'ivfflat': Inverted File with Flat compression (good for large datasets)
    'hnsw'
    
    ivfflat?: IVFFlatConfig

    IVFFlat-specific configuration parameters. Only used when indexType is 'ivfflat'.