})
s3://hub-2.0-datasets-n/langchain_test loaded successfully.
Evaluating ingest: 100%|██████████| 1/1 [00:10<00:00
\
Dataset(path='s3://hub-2.0-datasets-n/langchain_test', tensors=['embedding', 'ids', 'metadata', 'text'])
  tensor     htype     shape     dtype  compression
  -------   -------   -------   -------  ------- 
 embedding  generic  (4, 1536)  float32   None   
    ids      text     (4, 1)      str     None   
 metadata    json     (4, 1)      str     None   
   text      text     (4, 1)      str     None   
 
Deep Lake API#
you can access the Deep Lake  dataset at db.ds
# get structure of the dataset
db.ds.summary()
Dataset(path='hub://davitbun/langchain_test', tensors=['embedding', 'ids', 'metadata', 'text'])
  tensor     htype     shape     dtype  compression
  -------   -------   -------   -------  ------- 
 embedding  generic  (4, 1536)  float32   None   
    ids      text     (4, 1)      str     None   
 metadata    json     (4, 1)      str     None   
   text      text     (4, 1)      str     None   
# get embeddings numpy array
embeds = db.ds.embedding.numpy()
Transfer local dataset to cloud#
Copy already created dataset to the cloud. You can also transfer from cloud to local.
import deeplake
username = "davitbun" # your username on app.activeloop.ai
rtdocs_stable/api.python.langchain.com/en/stable/modules/indexes/vectorstores/examples/deeplake.html