Type Alias VectorStoreRetrieverInput<V>

Input configuration options for creating a VectorStoreRetriever instance.

This type combines properties from BaseRetrieverInput with specific settings for the VectorStoreRetriever, including options for similarity or maximal marginal relevance (MMR) search types.

Fields:

• callbacks (optional): An array of callback functions that handle various events during retrieval, such as logging, error handling, or progress updates.

• tags (optional): An array of strings used to add contextual tags to retrieval operations, allowing for easier categorization and tracking.

• metadata (optional): A record of key-value pairs to store additional contextual information for retrieval operations, which can be useful for logging or auditing purposes.

• verbose (optional): A boolean flag that, if set to true, enables detailed logging and output during the retrieval process. Defaults to false.

• vectorStore: The VectorStore instance implementing VectorStoreInterface that will be used for document storage and retrieval.

• k (optional): Specifies the number of documents to retrieve per search query. Defaults to 4 if not specified.

• filter (optional): A filter of type FilterType (defined by the vector store) to refine the set of documents returned, allowing for targeted search results.

• searchType: Determines the type of search to perform:

  • "similarity": Executes a similarity search, retrieving documents based purely on vector similarity to the query.
  • "mmr": Executes a maximal marginal relevance (MMR) search, balancing similarity and diversity in the search results.

• searchKwargs (optional): Used only if searchType is "mmr", this object provides additional options for MMR search, including:

  • fetchK: Specifies the number of documents to initially fetch before applying the MMR algorithm, providing a pool from which the most diverse results are selected.
  • lambda: A diversity parameter, where 0 emphasizes diversity and 1 emphasizes relevance to the query. Values between 0 and 1 provide a balance of relevance and diversity.