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        • Step 1: Hello World
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    • RAG
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        • Vector Store Basics
        • Vector Search Options
          • LangChain API
          • Deep Lake Vector Store API
          • Managed Database REST API
        • Customizing Your Vector Store
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      • LangChain Integration
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        • REST API
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        • How it Works
    • Tensor Query Language (TQL)
      • TQL Syntax
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    • Best Practices
      • Creating Datasets at Scale
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      • Storage Synchronization and "with" Context
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        • Concurrency Using Zookeeper Locks
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      • Tensor Relationships
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    • Dataset Visualization
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    • Shuffling in Dataloaders
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  • Overview of Vector Search Options in Deep Lake
  • APIs for Search
  • Overview of Options for Search Computation Execution

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  1. Examples
  2. RAG
  3. RAG Tutorials

Vector Search Options

Overview of Vector Search Options in Deep Lake

PreviousVector Store BasicsNextLangChain API

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Overview of Vector Search Options in Deep Lake

Deep Lake offers a variety of vector search options depending on the of the Vector Store and infrastructure that should run the computations.

Storage Location
Compute Location
Execution Algorithm

In memory or local

Client-side

Deep Lake OSS Python Code

Client-side

Deep Lake C++

Deep Lake Storage

Client-side

Deep Lake C++

Deep Lake Managed Tensor Database

Managed Database

Deep Lake C++

APIs for Search

Vector search can occur via a variety of APIs in Deep Lake. They are explained in the links below:

Overview of Options for Search Computation Execution

The optimal option for search execution is automatically selected based on the Vector Stores storage location. The different computation options are explained below.

Python (Client-Side)

Deep Lake OSS offers query execution logic that run on the client (your machine) using OSS code in Python. This compute logic is accessible in all Deep Lake Python APIs and is available for Vector Stores stored in any location. See individual APIs below for details.

Compute Engine (Client-Side)

To run queries using Compute Engine, make sure to !pip install "deeplake[enterprise]".

Managed Tensor Database (Server-Side Running Compute Engine)

Deep Lake offers a Managed Tensor Database that executes queries on Deep Lake infrastructure while running Compute Engine under-the-hood. This compute logic is accessible in all Deep Lake Python APIs and is only available for Vector Stores stored in the Deep Lake Managed Tensor Database. See individual APIs below for details.

User cloud ()

Deep Lake Compute Engine offers query execution logic that run on the client (your machine) using C++ Code that is called via Python API. This compute logic is accessible in all Deep Lake Python APIs and is only available for Vector Stores stored Deep Lake storage or in user clouds . See individual APIs below for details.

📚
Storage Location
Deep Lake Vector Store API
Managed Database REST API
LangChain API
connected to Deep Lake
must be connected to Deep Lake