ProvidersMoreActiveloop Deep LakeOn this pageActiveloop Deep LakeThis 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.)Activeloop Deep Lake supports SelfQuery Retrieval:
Activeloop Deep Lake Self Query RetrievalMore Resources​Ultimate Guide to LangChain & Deep Lake: Build ChatGPT to Answer Questions on Your Financial DataTwitter the-algorithm codebase analysis with Deep LakeCode UnderstandingHere is whitepaper and academic paper for Deep LakeHere is a set of additional resources available for review: Deep Lake, Get started and TutorialsInstallation and Setup​Install the Python package with pip install deeplakeWrappers​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 DeepLakeFor a more detailed walkthrough of the Deep Lake wrapper, see this notebookPreviousOpenAINextAI21 LabsWhy Deep Lake?More ResourcesInstallation and SetupWrappersVectorStore