langchain.vectorstores.redis.RedisVectorStoreRetriever¶
class langchain.vectorstores.redis.RedisVectorStoreRetriever[source]¶
Bases: VectorStoreRetriever
Retriever for Redis VectorStore.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param k: int = 4¶
Number of documents to return.
param metadata: Optional[Dict[str, Any]] = None¶
Optional metadata associated with the retriever. Defaults to None
This metadata will be associated with each call to this retriever,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a retriever with its
use case.
param score_threshold: float = 0.4¶
Score threshold for similarity_limit search.
param search_kwargs: dict [Optional]¶
Keyword arguments to pass to the search function.
param search_type: str = 'similarity'¶
Type of search to perform. Can be either ‘similarity’ or ‘similarity_limit’.
param tags: Optional[List[str]] = None¶
Optional list of tags associated with the retriever. Defaults to None
These tags will be associated with each call to this retriever,
and passed as arguments to the handlers defined in callbacks.
You can use these to eg identify a specific instance of a retriever with its
use case.
param vectorstore: Redis [Required]¶
Redis VectorStore.
async aadd_documents(documents: List[Document], **kwargs: Any) → List[str][source]¶
Add documents to vectorstore.