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.
