Creates an empty DeepLakeVectorStore or loads an existing one.
The DeepLakeVectorStore is located at the specified path.
Examples
>>> # Create a vector store with default tensors
>>> deeplake_vectorstore = DeepLake(
...        path = <path_for_storing_Data>,
... )
>>>
>>> # Create a vector store in the Deep Lake Managed Tensor Database
>>> data = DeepLake(
...        path = "hub://org_id/dataset_name",
...        exec_option = "tensor_db",
... )
Parameters
dataset_path (str) – Path to existing dataset or where to create
a new one. Defaults to _LANGCHAIN_DEFAULT_DEEPLAKE_PATH.
token (str, optional) – Activeloop token, for fetching credentials
to the dataset at path if it is a Deep Lake dataset.
Tokens are normally autogenerated. Optional.
embedding (Embeddings, optional) – Function to convert
either documents or query. Optional.
embedding_function (Embeddings, optional) – Function to convert
either documents or query. Optional. Deprecated: keeping this
parameter for backwards compatibility.
read_only (bool) – Open dataset in read-only mode. Default is False.
ingestion_batch_size (int) – During data ingestion, data is divided
into batches. Batch size is the size of each batch.
Default is 1000.
num_workers (int) – Number of workers to use during data ingestion.
Default is 0.
verbose (bool) – Print dataset summary after each operation.
Default is True.
exec_option (str, optional) – DeepLakeVectorStore supports 3 ways to perform
searching - “python”, “compute_engine”, “tensor_db” and auto.
Default is None.
- auto- Selects the best execution method based on the storage