lambda_mult – Number between 0 and 1 determining the degree of diversity.
0 corresponds to max diversity and 1 to min diversity. Defaults to 0.5.
exec_option (str) – DeepLakeVectorStore supports 3 ways for searching.
Could be “python”, “compute_engine” or “tensor_db”. Defaults to
“python”.
- “python” - Pure-python implementation running on the client.
Can be used for data stored anywhere. WARNING: using this
option with big datasets is discouraged due to potential
memory issues.
”compute_engine” - Performant C++ implementation of the DeepLake Compute Engine. Runs on the client and can be used for
any data stored in or connected to Deep Lake. It cannot be used
with in-memory or local datasets.
”tensor_db” - Performant, fully-hosted Managed Tensor Database.Responsible for storage and query execution. Only available for
data stored in the Deep Lake Managed Database. To store datasets
in this database, specify runtime = {“db_engine”: True}
during dataset creation.
deep_memory (bool) – Whether to use the Deep Memory model for improving
search results. Defaults to False if deep_memory is not specified
in the Vector Store initialization. If True, the distance metric
is set to “deepmemory_distance”, which represents the metric with
which the model was trained. The search is performed using the Deep
Memory model. If False, the distance metric is set to “COS” or
whatever distance metric user specifies.
**kwargs – Additional keyword arguments.
Returns
List[Documents] - A list of documents.
search(query: str, search_type: str, **kwargs: Any) → List[Document]¶
Return docs most similar to query using specified search type.