langchain.vectorstores.azuresearch.AzureSearchVectorStoreRetriever¶
class langchain.vectorstores.azuresearch.AzureSearchVectorStoreRetriever[source]¶
Bases: BaseRetriever
Retriever that uses Azure Search to find similar documents.
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 search_type: str = 'hybrid'¶
Type of search to perform. Options are “similarity”, “hybrid”,
“semantic_hybrid”.
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: langchain.vectorstores.azuresearch.AzureSearch [Required]¶
Azure Search instance used to find similar documents.
async abatch(inputs: List[Input], config: Optional[Union[RunnableConfig, List[RunnableConfig]]] = None, *, max_concurrency: Optional[int] = None) → List[Output]¶