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

constructor

• new ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>(embeddings, config): ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>

• 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

  • embeddings: EmbeddingsInterface

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

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

FilterType

addDocuments

• addDocuments(documents): Promise<void>

• 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[]

    Documents to be added.

  Returns Promise<void>

  Promise that resolves when the documents have been added.

addVectors

• addVectors(vectors, documents): Promise<void>

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

  Parameters

  • vectors: number[][]

    Vectors to be added.

  • documents: Document[]

    Corresponding documents to be added.

  Returns Promise<void>

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

similaritySearchVectorWithScore

• similaritySearchVectorWithScore(query, k, filter?): Promise<[Document, number][]>

• 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, number][]>

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

Static fromDocuments

• fromDocuments<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>(docs, embeddings, dbConfig): Promise<ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>>

• 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[]

    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

• fromTexts<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>(texts, metadatas, embeddings, dbConfig): Promise<ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>>

• 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.