Class AnalyticDBVectorStore

constructor

• new AnalyticDBVectorStore(embeddings, args): AnalyticDBVectorStore

• Parameters

  • embeddings: EmbeddingsInterface

  • args: AnalyticDBArgs

  Returns AnalyticDBVectorStore

FilterType

addDocuments

• addDocuments(documents): Promise<void>

• Adds an array of documents to the collection. The documents are first converted to vectors using the embedDocuments method of the embeddings instance.

  Parameters

  • documents: Document[]

    Array of Document instances to be added to the collection.

  Returns Promise<void>

  Promise that resolves when the documents are added.

addVectors

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

• Adds an array of vectors and corresponding documents to the collection. The vectors and documents are batch inserted into the database.

  Parameters

  • vectors: number[][]

    Array of vectors to be added to the collection.

  • documents: Document[]

    Array of Document instances corresponding to the vectors.

  Returns Promise<void>

  Promise that resolves when the vectors and documents are added.

createCollection

• createCollection(): Promise<void>

• Creates a new collection in the database. If preDeleteCollection is true, any existing collection with the same name is deleted before the new collection is created.

  Returns Promise<void>

  Promise that resolves when the collection is created.

createTableIfNotExists

• createTableIfNotExists(): Promise<void>

• Creates a new table in the database if it does not already exist. The table is created with columns for id, embedding, document, and metadata. An index is also created on the embedding column if it does not already exist.

  Returns Promise<void>

  Promise that resolves when the table and index are created.

deleteCollection

• deleteCollection(): Promise<void>

• Deletes the collection from the database if it exists.

  Returns Promise<void>

  Promise that resolves when the collection is deleted.

end

• end(): Promise<void>

• Closes all the clients in the pool and terminates the pool.

  Returns Promise<void>

  Promise that resolves when all clients are closed and the pool is terminated.

similaritySearchVectorWithScore

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

• Performs a similarity search on the vectors in the collection. The search is performed using the given query vector and returns the top k most similar vectors along with their corresponding documents and similarity scores.

  Parameters

  • query: number[]

    Query vector for the similarity search.

  • k: number

    Number of top similar vectors to return.

  • Optional filter: Record<string, any>

    Optional. Filter to apply on the metadata of the documents.

  Returns Promise<[Document, number][]>

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

Static fromDocuments

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

• Creates an instance of AnalyticDBVectorStore from an array of Document instances. The documents are added to the collection.

  Parameters

  • docs: Document[]

    Array of Document instances to be added to the collection.

  • embeddings: EmbeddingsInterface

    Embeddings instance used to convert the documents to vectors.

  • dbConfig: AnalyticDBArgs

    Configuration for the AnalyticDB.

  Returns Promise<AnalyticDBVectorStore>

  Promise that resolves to an instance of AnalyticDBVectorStore.

Static fromExistingIndex

• fromExistingIndex(embeddings, dbConfig): Promise<AnalyticDBVectorStore>

• Creates an instance of AnalyticDBVectorStore from an existing index in the database. A new collection is created in the database.

  Parameters

  • embeddings: EmbeddingsInterface

    Embeddings instance used to convert the documents to vectors.

  • dbConfig: AnalyticDBArgs

    Configuration for the AnalyticDB.

  Returns Promise<AnalyticDBVectorStore>

  Promise that resolves to an instance of AnalyticDBVectorStore.

Static fromTexts

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

• Creates an instance of AnalyticDBVectorStore from an array of texts and corresponding metadata. The texts are first converted to Document instances before being added to the collection.

  Parameters

  • texts: string[]

    Array of texts to be added to the collection.

  • metadatas: object | object[]

    Array or object of metadata corresponding to the texts.

  • embeddings: EmbeddingsInterface

    Embeddings instance used to convert the texts to vectors.

  • dbConfig: AnalyticDBArgs

    Configuration for the AnalyticDB.

  Returns Promise<AnalyticDBVectorStore>

  Promise that resolves to an instance of AnalyticDBVectorStore.