username = "<username>" # your username on app.activeloop.ai   
dataset_path = f"hub://{username}/langchain_test" # could be also ./local/path (much faster locally), s3://bucket/path/to/dataset, gcs://path/to/dataset, etc.
embedding = OpenAIEmbeddings()
db = DeepLake(dataset_path=dataset_path, embedding_function=embeddings, overwrite=True)
db.add_documents(docs)
Your Deep Lake dataset has been successfully created!
The dataset is private so make sure you are logged in!
This dataset can be visualized in Jupyter Notebook by ds.visualize() or at https://app.activeloop.ai/davitbun/langchain_test
hub://davitbun/langchain_test loaded successfully.
Evaluating ingest: 100%|██████████| 1/1 [00:14<00:00
 
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   
['d6d6ccb4-e187-11ed-b66d-41c5f7b85421',
 'd6d6ccb5-e187-11ed-b66d-41c5f7b85421',
 'd6d6ccb6-e187-11ed-b66d-41c5f7b85421',
rtdocs_stable/api.python.langchain.com/en/stable/modules/indexes/vectorstores/examples/deeplake.html