Class MemoryVectorStore

constructor

• new MemoryVectorStore(embeddings, __namedParameters?): MemoryVectorStore

• Parameters

  • embeddings: EmbeddingsInterface
  • __namedParameters: MemoryVectorStoreArgs = {}

  Returns MemoryVectorStore

FilterType

memoryVectors

similarity

addDocuments

• addDocuments(documents): Promise<void>

• Method to add documents to the memory vector store. It extracts the text from each document, generates embeddings for them, and adds the resulting vectors to the store.

  Parameters

  • documents: Document[]

    Array of Document instances to be added to the store.

  Returns Promise<void>

  Promise that resolves when all documents have been added.

addVectors

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

• Method to add vectors to the memory vector store. It creates MemoryVector instances for each vector and document pair and adds them to the store.

  Parameters

  • vectors: number[][]

    Array of vectors to be added to the store.
  • documents: Document[]

    Array of Document instances corresponding to the vectors.

  Returns Promise<void>

  Promise that resolves when all vectors have been added.

similaritySearchVectorWithScore

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

• Method to perform a similarity search in the memory vector store. It calculates the similarity between the query vector and each vector in the store, sorts the results by similarity, and returns the top k results along with their scores.

  Parameters

  • query: number[]

    Query vector to compare against the vectors in the store.
  • k: number

    Number of top results to return.
  • Optionalfilter: ((doc: Document) => boolean)

    Optional filter function to apply to the vectors before performing the search.

    • • (doc): boolean

      • Parameters

        • doc: Document

        Returns boolean

  Returns Promise<[Document, number][]>

  Promise that resolves with an array of tuples, each containing a Document and its similarity score.

StaticfromDocuments

• fromDocuments(docs, embeddings, dbConfig?): Promise<MemoryVectorStore>

• Static method to create a MemoryVectorStore instance from an array of Document instances. It adds the documents to the store.

  Parameters

  • docs: Document[]

    Array of Document instances to be added to the store.
  • embeddings: EmbeddingsInterface

    Embeddings instance used to generate embeddings for the documents.
  • OptionaldbConfig: MemoryVectorStoreArgs

    Optional MemoryVectorStoreArgs to configure the MemoryVectorStore instance.

  Returns Promise<MemoryVectorStore>

  Promise that resolves with a new MemoryVectorStore instance.

StaticfromExistingIndex

• fromExistingIndex(embeddings, dbConfig?): Promise<MemoryVectorStore>

• Static method to create a MemoryVectorStore instance from an existing index. It creates a new MemoryVectorStore instance without adding any documents or vectors.

  Parameters

  • embeddings: EmbeddingsInterface

    Embeddings instance used to generate embeddings for the documents.
  • OptionaldbConfig: MemoryVectorStoreArgs

    Optional MemoryVectorStoreArgs to configure the MemoryVectorStore instance.

  Returns Promise<MemoryVectorStore>

  Promise that resolves with a new MemoryVectorStore instance.

StaticfromTexts

• fromTexts(texts, metadatas, embeddings, dbConfig?): Promise<MemoryVectorStore>

• Static method to create a MemoryVectorStore instance from an array of texts. It creates a Document for each text and metadata pair, and adds them to the store.

  Parameters

  • texts: string[]

    Array of texts to be added to the store.
  • metadatas: object | object[]

    Array or single object of metadata corresponding to the texts.
  • embeddings: EmbeddingsInterface

    Embeddings instance used to generate embeddings for the texts.
  • OptionaldbConfig: MemoryVectorStoreArgs

    Optional MemoryVectorStoreArgs to configure the MemoryVectorStore instance.

  Returns Promise<MemoryVectorStore>

  Promise that resolves with a new MemoryVectorStore instance.