Activeloop Deep Lake is a data lake for Deep Learning applications, allowing you to use it as a vector store.

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Why Deep Lake?

  • More than just a (multi-modal) vector store. You can later use the dataset to fine-tune your own LLM models.
  • Not only stores embeddings, but also the original data with automatic version control.
  • Truly serverless. Doesn’t require another service and can be used with major cloud providers (AWS S3, GCS, etc.)
Activeloop Deep Lake supports SelfQuery Retrieval: Activeloop Deep Lake Self Query Retrieval

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More Resources

  1. Ultimate Guide to LangChain & Deep Lake: Build ChatGPT to Answer Questions on Your Financial Data
  2. Twitter the-algorithm codebase analysis with Deep Lake
  3. Here is whitepaper and academic paper for Deep Lake
  4. Here is a set of additional resources available for review: Deep Lake, Get started and Tutorials

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Installation and Setup

Install the Python package: 
pip install deeplake

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VectorStore

from langchain_community.vectorstores import DeepLake
See a usage example.