langchain/docs/integrations/deeplake.md
Leonid Ganeline e2d7677526
docs: compound ecosystem and integrations (#4870)
# Docs: compound ecosystem and integrations

**Problem statement:** We have a big overlap between the
References/Integrations and Ecosystem/LongChain Ecosystem pages. It
confuses users. It creates a situation when new integration is added
only on one of these pages, which creates even more confusion.
- removed References/Integrations page (but move all its information
into the individual integration pages - in the next PR).
- renamed Ecosystem/LongChain Ecosystem into Integrations/Integrations.
I like the Ecosystem term. It is more generic and semantically richer
than the Integration term. But it mentally overloads users. The
`integration` term is more concrete.
UPDATE: after discussion, the Ecosystem is the term.
Ecosystem/Integrations is the page (in place of Ecosystem/LongChain
Ecosystem).

As a result, a user gets a single place to start with the individual
integration.
2023-05-18 09:29:57 -07:00

1.7 KiB

Deep Lake

This page covers how to use the Deep Lake ecosystem within LangChain.

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.)

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, Getting Started and Tutorials

Installation and Setup

  • Install the Python package with pip install deeplake

Wrappers

VectorStore

There exists a wrapper around Deep Lake, a data lake for Deep Learning applications, allowing you to use it as a vector store (for now), whether for semantic search or example selection.

To import this vectorstore:

from langchain.vectorstores import DeepLake

For a more detailed walkthrough of the Deep Lake wrapper, see this notebook