Class ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>

Class that is a wrapper around Convex storage and vector search. It is used to insert embeddings in Convex documents with a vector search index, and perform a vector search on them.

ConvexVectorStore does NOT implement maxMarginalRelevanceSearch.

Type Parameters

  • DataModel extends GenericDataModel

  • TableName extends TableNamesInDataModel<DataModel>

  • IndexName extends VectorIndexNames<NamedTableInfo<DataModel, TableName>>

  • TextFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>

  • EmbeddingFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>

  • MetadataFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>

  • InsertMutation extends FunctionReference<"mutation", "internal", {
        document: object;
        table: string;
    }>

  • GetQuery extends FunctionReference<"query", "internal", {
        id: string;
    }, object | null>

Hierarchy

Constructors

constructor

Properties

FilterType embeddings

Methods

addDocuments addVectors asRetriever delete similaritySearch similaritySearchVectorWithScore similaritySearchWithScore toJSON toJSONNotImplemented maxMarginalRelevanceSearch? fromDocuments fromTexts

Constructors

constructor

  • Type Parameters

    • DataModel extends GenericDataModel

    • TableName extends string

    • IndexName extends string | number | symbol

    • TextFieldName extends string

    • EmbeddingFieldName extends string

    • MetadataFieldName extends string

    • InsertMutation extends FunctionReference<"mutation", "internal", {
          document: object;
          table: string;
      }>

    • GetQuery extends FunctionReference<"query", "internal", {
          id: string;
      }, null | object>

    Parameters

    Returns ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>

Properties

FilterType

FilterType: {
    filter?: ((q) => FilterExpression<boolean>);
    includeEmbeddings?: boolean;
}

Type that defines the filter used in the similaritySearchVectorWithScore and maxMarginalRelevanceSearch methods. It includes limit, filter and a flag to include embeddings.

Type declaration

  • Optional filter?: ((q) => FilterExpression<boolean>)
      • (q): FilterExpression<boolean>

      • Parameters

        • q: VectorFilterBuilder<GenericDocument, NamedVectorIndex<NamedTableInfo<DataModel, TableName>, IndexName>>

        Returns FilterExpression<boolean>

  • Optional includeEmbeddings?: boolean

embeddings

embeddings: EmbeddingsInterface

Methods

addDocuments

  • Add documents to the Convex table. It first converts the documents to vectors using the embeddings and then calls the addVectors method.

    Parameters

    • documents: Document<Record<string, any>>[]

      Documents to be added.

    Returns Promise<void>

    Promise that resolves when the documents have been added.

addVectors

  • Add vectors and their corresponding documents to the Convex table.

    Parameters

    • vectors: number[][]

      Vectors to be added.

    • documents: Document<Record<string, any>>[]

      Corresponding documents to be added.

    Returns Promise<void>

    Promise that resolves when the vectors and documents have been added.

asRetriever

  • Parameters

    • Optional kOrFields: number | Partial<VectorStoreRetrieverInput<ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>>>
    • Optional filter: {
          filter?: ((q) => FilterExpression<boolean>);
          includeEmbeddings?: boolean;
      }
      • Optional filter?: ((q) => FilterExpression<boolean>)
          • (q): FilterExpression<boolean>

          • Parameters

            • q: VectorFilterBuilder<GenericDocument, NamedVectorIndex<NamedTableInfo<DataModel, TableName>, IndexName>>

            Returns FilterExpression<boolean>

      • Optional includeEmbeddings?: boolean
    • Optional callbacks: Callbacks
    • Optional tags: string[]
    • Optional metadata: Record<string, unknown>
    • Optional verbose: boolean

    Returns VectorStoreRetriever<ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>>

delete

  • Parameters

    • Optional _params: Record<string, any>

    Returns Promise<void>

similaritySearch

  • Parameters

    • query: string
    • Optional k: number
    • Optional filter: {
          filter?: ((q) => FilterExpression<boolean>);
          includeEmbeddings?: boolean;
      }
      • Optional filter?: ((q) => FilterExpression<boolean>)
          • (q): FilterExpression<boolean>

          • Parameters

            • q: VectorFilterBuilder<GenericDocument, NamedVectorIndex<NamedTableInfo<DataModel, TableName>, IndexName>>

            Returns FilterExpression<boolean>

      • Optional includeEmbeddings?: boolean
    • Optional _callbacks: Callbacks

    Returns Promise<DocumentInterface<Record<string, any>>[]>

similaritySearchVectorWithScore

  • Similarity search on the vectors stored in the Convex table. It returns a list of documents and their corresponding similarity scores.

    Parameters

    • query: number[]

      Query vector for the similarity search.

    • k: number

      Number of nearest neighbors to return.

    • Optional filter: {
          filter?: ((q) => FilterExpression<boolean>);
          includeEmbeddings?: boolean;
      }

      Optional filter to be applied.

      • Optional filter?: ((q) => FilterExpression<boolean>)
          • (q): FilterExpression<boolean>

          • Parameters

            • q: VectorFilterBuilder<GenericDocument, NamedVectorIndex<NamedTableInfo<DataModel, TableName>, IndexName>>

            Returns FilterExpression<boolean>

      • Optional includeEmbeddings?: boolean

    Returns Promise<[Document<Record<string, any>>, number][]>

    Promise that resolves to a list of documents and their corresponding similarity scores.

similaritySearchWithScore

  • Parameters

    • query: string
    • Optional k: number
    • Optional filter: {
          filter?: ((q) => FilterExpression<boolean>);
          includeEmbeddings?: boolean;
      }
      • Optional filter?: ((q) => FilterExpression<boolean>)
          • (q): FilterExpression<boolean>

          • Parameters

            • q: VectorFilterBuilder<GenericDocument, NamedVectorIndex<NamedTableInfo<DataModel, TableName>, IndexName>>

            Returns FilterExpression<boolean>

      • Optional includeEmbeddings?: boolean
    • Optional _callbacks: Callbacks

    Returns Promise<[DocumentInterface<Record<string, any>>, number][]>

toJSON

toJSONNotImplemented

Optional maxMarginalRelevanceSearch

  • Return documents selected using the maximal marginal relevance. Maximal marginal relevance optimizes for similarity to the query AND diversity among selected documents.

    Parameters

    • query: string

      Text to look up documents similar to.

    • options: MaxMarginalRelevanceSearchOptions<{
          filter?: ((q) => FilterExpression<boolean>);
          includeEmbeddings?: boolean;
      }>
    • _callbacks: undefined | Callbacks

    Returns Promise<DocumentInterface<Record<string, any>>[]>

    • List of documents selected by maximal marginal relevance.

Static fromDocuments

  • Static method to create an instance of ConvexVectorStore from a list of documents. It first converts the documents to vectors and then adds them to the Convex table.

    Type Parameters

    • DataModel extends GenericDataModel

    • TableName extends string

    • IndexName extends string | number | symbol

    • TextFieldName extends string

    • EmbeddingFieldName extends string

    • MetadataFieldName extends string

    • InsertMutation extends FunctionReference<"mutation", "internal", {
          document: object;
          table: string;
      }>

    • GetQuery extends FunctionReference<"query", "internal", {
          id: string;
      }, null | object>

    Parameters

    • docs: Document<Record<string, any>>[]

      List of documents to be converted to vectors.

    • embeddings: EmbeddingsInterface

      Embeddings to be used for conversion.

    • dbConfig: ConvexVectorStoreConfig<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>

      Database configuration for Convex.

    Returns Promise<ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>>

    Promise that resolves to a new instance of ConvexVectorStore.

Static fromTexts

  • Static method to create an instance of ConvexVectorStore from a list of texts. It first converts the texts to vectors and then adds them to the Convex table.

    Type Parameters

    • DataModel extends GenericDataModel

    • TableName extends string

    • IndexName extends string | number | symbol

    • TextFieldName extends string

    • EmbeddingFieldName extends string

    • MetadataFieldName extends string

    • InsertMutation extends FunctionReference<"mutation", "internal", {
          document: object;
          table: string;
      }>

    • GetQuery extends FunctionReference<"query", "internal", {
          id: string;
      }, null | object>

    Parameters

    • texts: string[]

      List of texts to be converted to vectors.

    • metadatas: object | object[]

      Metadata for the texts.

    • embeddings: EmbeddingsInterface

      Embeddings to be used for conversion.

    • dbConfig: ConvexVectorStoreConfig<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>

      Database configuration for Convex.

    Returns Promise<ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>>

    Promise that resolves to a new instance of ConvexVectorStore.

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