text: EndpointSearxNG Search APISerpAPIShale ProtocolSingleStoreDBscikit-learnSlackspaCySpreedlyStarRocksStochasticAIStripeTairTelegramTigris2MarkdownTrelloTruLensTwitterTypesenseUnstructuredVectaraVespaWeights & BiasesWeatherWeaviateWhatsAppWhyLabsWikipediaWolfram AlphaWriterYeager.aiYouTubeZepZillizIntegrationsGrouped by providerDeep LakeOn this pageDeep LakeThis page covers how to use the Deep Lake ecosystem within LangChain.Why Deep Lake?â€‹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 Resourcesâ€‹Ultimate Guide to LangChain & Deep Lake: Build ChatGPT to Answer Questions on Your Financial DataTwitter the-algorithm codebase analysis with Deep LakeHere is whitepaper and academic paper for Deep LakeHere is a set of additional resources available for review: Deep Lake, Get started andÂ TutorialsInstallation and Setupâ€‹Install the Python package with pip install deeplakeWrappersâ€‹VectorStoreâ€‹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 notebookPreviousDeepInfraNextDiffbotWhy Deep Lake?More ResourcesInstallation and SetupWrappersVectorStoreCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.