Interface EmbeddingStore

  • All Implemented Interfaces:

    
    public interface EmbeddingStore<Embedded>
    
                        

    Represents a store for embeddings, also known as a vector database.

    • Constructor Detail

    • Method Detail

      • add

         abstract String add(Embedding embedding)

        Adds a given embedding to the store.

        Parameters:
        embedding - The embedding to be added to the store.
        Returns:

        The auto-generated ID associated with the added embedding.

      • add

         abstract void add(String id, Embedding embedding)

        Adds a given embedding to the store.

        Parameters:
        id - The unique identifier for the embedding to be added.
        embedding - The embedding to be added to the store.
      • add

         abstract String add(Embedding embedding, Embedded embedded)

        Adds a given embedding and the corresponding content that has been embedded to the store.

        Parameters:
        embedding - The embedding to be added to the store.
        embedded - Original content that was embedded.
        Returns:

        The auto-generated ID associated with the added embedding.

      • addAll

         abstract List<String> addAll(List<Embedding> embeddings)

        Adds multiple embeddings to the store.

        Parameters:
        embeddings - A list of embeddings to be added to the store.
        Returns:

        A list of auto-generated IDs associated with the added embeddings.

      • addAll

         List<String> addAll(List<Embedding> embeddings, List<Embedded> embedded)

        Adds multiple embeddings and their corresponding contents that have been embedded to the store.

        Parameters:
        embeddings - A list of embeddings to be added to the store.
        embedded - A list of original contents that were embedded.
        Returns:

        A list of auto-generated IDs associated with the added embeddings.

      • addAll

         void addAll(List<String> ids, List<Embedding> embeddings, List<Embedded> embedded)

        Adds multiple embeddings and their corresponding contents that have been embedded to the store.

        Parameters:
        ids - A list of IDs associated with the added embeddings.
        embeddings - A list of embeddings to be added to the store.
        embedded - A list of original contents that were embedded.
      • remove

         void remove(String id)

        Removes a single embedding from the store by ID.

        Parameters:
        id - The unique ID of the embedding to be removed.
      • removeAll

         void removeAll(Collection<String> ids)

        Removes all embeddings that match the specified IDs from the store.

        Parameters:
        ids - A collection of unique IDs of the embeddings to be removed.
      • removeAll

         void removeAll(Filter filter)

        Removes all embeddings that match the specified Filter from the store.

        Parameters:
        filter - The filter to be applied to the Metadata of the TextSegment during removal.
      • removeAll

         void removeAll()

        Removes all embeddings from the store.

      • generateIds

         List<String> generateIds(int n)

        Generates list of UUID strings

        Parameters:
        n - - dimension of list
      • findRelevant

        @Deprecated(forRemoval = true) List<EmbeddingMatch<Embedded>> findRelevant(Embedding referenceEmbedding, int maxResults)

        Finds the most relevant (closest in space) embeddings to the provided reference embedding. By default, minScore is set to 0, which means that the results may include embeddings with low relevance.

        Parameters:
        referenceEmbedding - The embedding used as a reference.
        maxResults - The maximum number of embeddings to be returned.
        Returns:

        A list of embedding matches. Each embedding match includes a relevance score (derivative of cosine distance), ranging from 0 (not relevant) to 1 (highly relevant).

      • findRelevant

        @Deprecated(forRemoval = true) List<EmbeddingMatch<Embedded>> findRelevant(Embedding referenceEmbedding, int maxResults, double minScore)

        Finds the most relevant (closest in space) embeddings to the provided reference embedding.

        Parameters:
        referenceEmbedding - The embedding used as a reference.
        maxResults - The maximum number of embeddings to be returned.
        minScore - The minimum relevance score, ranging from 0 to 1 (inclusive).
        Returns:

        A list of embedding matches. Each embedding match includes a relevance score (derivative of cosine distance), ranging from 0 (not relevant) to 1 (highly relevant).

      • findRelevant

        @Deprecated(forRemoval = true) List<EmbeddingMatch<Embedded>> findRelevant(Object memoryId, Embedding referenceEmbedding, int maxResults)

        Finds the most relevant (closest in space) embeddings to the provided reference embedding. By default, minScore is set to 0, which means that the results may include embeddings with low relevance.

        Parameters:
        memoryId - The memoryId used Distinguishing query requests from different users.
        referenceEmbedding - The embedding used as a reference.
        maxResults - The maximum number of embeddings to be returned.
        Returns:

        A list of embedding matches. Each embedding match includes a relevance score (derivative of cosine distance), ranging from 0 (not relevant) to 1 (highly relevant).

      • findRelevant

        @Deprecated(forRemoval = true) List<EmbeddingMatch<Embedded>> findRelevant(Object memoryId, Embedding referenceEmbedding, int maxResults, double minScore)

        Finds the most relevant (closest in space) embeddings to the provided reference embedding.

        Parameters:
        memoryId - The memoryId used Distinguishing query requests from different users.
        referenceEmbedding - The embedding used as a reference.
        maxResults - The maximum number of embeddings to be returned.
        minScore - The minimum relevance score, ranging from 0 to 1 (inclusive).
        Returns:

        A list of embedding matches. Each embedding match includes a relevance score (derivative of cosine distance), ranging from 0 (not relevant) to 1 (highly relevant).