deeplake 3.9.0

Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more.

Stars: 7666, Watchers: 7666, Forks: 584, Open Issues: 69

The activeloopai/deeplake repo was created 4 years ago and the last code push was 3 days ago.
The project is extremely popular with a mindblowing 7666 github stars!

How to Install deeplake

You can install deeplake using pip

pip install deeplake

or add it to a project with poetry

poetry add deeplake

Package Details

Author

activeloop.ai

License

MPL-2.0

Homepage

None

PyPi:

https://pypi.org/project/deeplake/

Documentation:

https://docs.activeloop.ai/

GitHub Repo:

https://github.com/activeloopai/deeplake

Classifiers

Related Packages

Errors

A list of common deeplake errors.

Code Examples

Here are some deeplake code examples and snippets.

GitHub Issues

The deeplake package has 69 open issues on GitHub

• Data fix
• [Tiny] Removed reporting when importing deeplake
• [BUG] Possibly unsafe conversion of DatasetDiff instance to bytes
• Better metadata search
• [BUG] Issue with ImageNet training set.
• [BUG] poetry add deeplake hangs - pip works fine
• Create SECURITY.md
• skip visualizer for python3.11
• [AL-2272] Concurrent writes
• Indexing deeplake
• Added support for audio/video support in hub.ingest
• [FEATURE] Redis storage provider

See more issues on GitHub