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LanceDB Documentation

lancedb/documentation

Documentation
Documentation
- Getting Started
  Getting Started
  - How to Use This Docsite
  - Quickstart
    
    Quickstart
    
    Basic Usage
    
    Working with Datasets
- Products
  Products
  - What is LanceDB OSS?
    
    What is LanceDB OSS?
    
    FAQs
  - LanceDB Cloud
    
    LanceDB Cloud
    
    Logging
    
    Cloud FAQ
  - LanceDB Enterprise
    
    LanceDB Enterprise
    
    Architecture
    
    Deployment
    
    Benchmark
    
    Security
    
    FAQ
- Core Usage
  Core Usage
  - Concepts
    Concepts
    
    Data
    
    Vectors
    
    Indexing
    
    Search
    
    Storage
  - Working with Tables
    
    Working with Tables
    
    Table Operations
    
    Data Operations
    
    Managing Schema
    
    Versioning Tables
    
    Ensuring Consistency
  - Building an Index
    Building an Index
    
    Vector Index
    
    Scalar Index
    
    Full Text Index
    
    Reindexing
    
    GPU Indexing
  - Structuring Queries
    Structuring Queries
    
    Vector Search
    
    Full-Text Search (Native)
    
    Full-Text Search (Tantivy)
    
    Hybrid Search
    
    Multivector Search
    
    Filtering
    
    SQL Queries
    
    Query Planning
  - Configuring Storage
- Advanced Usage
  Advanced Usage
  - Complex Queries
    Complex Queries
    
    Hybrid Search
    Hybrid Search
    
    Comparing Rerankers
    
    Example - Airbnb financial data search
    
    Multivector Search
    Multivector Search
    
    Multivector Search: Efficient Document Retrieval with ColPali and LanceDB
    
    Reranking
    
    Reranking
    
    Cohere Reranker
    
    Linear Combination Reranker
    
    Reciprocal Rank Fusion Reranker
    
    Cross Encoder Reranker
    
    ColBERT Reranker
    
    Jina Reranker
    
    OpenAI Reranker
    
    AnswerDotAi Rerankers
    
    Voyage AI Rerankers
    
    Building Custom Rerankers
    
    Example
    
    Optimizing Query Performance
  - Working with Embeddings
    
    Working with Embeddings
    
    What are Embeddings?
    
    Embedding Models
    
    Available Models
    Available Models
    
    Overview
    
    Text Embedding Models
    Text Embedding Models
    
    Sentence Transformers
    
    Huggingface Embedding Models
    
    Ollama Embeddings
    
    OpenAI Embeddings
    
    Instructor Embeddings
    
    Gemini Embeddings
    
    Cohere Embeddings
    
    Jina Embeddings
    
    AWS Bedrock Text Embedding Functions
    
    IBM watsonx.ai Embeddings
    
    Voyage AI Embeddings
    
    Multimodal Embedding Models
    Multimodal Embedding Models
    
    OpenClip embeddings
    
    Imagebind embeddings
    
    Jina Embeddings
    
    User-Defined Embedding Models
    
    Variables and Secrets
  - Versioning & Reproducibility
    Versioning & Reproducibility
    
    Versioning Guide
    
    Sync API
    
    Async API
Tutorials & Integrations
Tutorials & Integrations
- Integrations
  Integrations
  - Platforms
    Platforms
    
    Pandas and PyArrow
    
    Polars
    
    DuckDB
    
    Voxel51
    
    dlt
    
    phidata
  - Embeddings
    Embeddings
    
    Available Models
    Available Models
    
    Overview
    
    Text Embedding Models
    Text Embedding Models
    
    Sentence Transformers
    
    Huggingface Embedding Models
    
    Ollama Embeddings
    
    OpenAI Embeddings
    
    Instructor Embeddings
    
    Gemini Embeddings
    
    Cohere Embeddings
    
    Jina Embeddings
    
    AWS Bedrock Text Embedding Functions
    
    IBM watsonx.ai Embeddings
    
    Voyage AI Embeddings
    
    Multimodal Embedding Models
    Multimodal Embedding Models
    
    OpenClip embeddings
    
    Imagebind embeddings
    
    Jina Embeddings
  - Rerankers
    
    Rerankers
    
    Cohere Reranker
    
    Linear Combination Reranker
    
    Reciprocal Rank Fusion Reranker
    
    Cross Encoder Reranker
    
    ColBERT Reranker
    
    Jina Reranker
    
    OpenAI Reranker
    
    AnswerDotAi Rerankers
    
    Voyage AI Rerankers
    
    Building Custom Rerankers
    
    Example - Improve Retrievers using Rerankers & Hybrid search
  - Frameworks
    Frameworks
    
    LangChain
    LangChain
    
    LangChain 🔗
    
    LangChain demo
    
    LangChain JS/TS 🔗
    
    LlamaIndex 🦙
    LlamaIndex 🦙
    
    LlamaIndex docs
    
    LlamaIndex demo
    
    Pydantic
    
    PromptTools
    
    Genkit
- Tutorials
  Tutorials
  - Python
    Python
    
    Overview
    
    Build From Scratch
    
    Multimodal
    
    Rag
    
    Vector Search
    
    Chatbot
    
    Evaluation
    
    AI Agent
    
    Recommender System
    
    Miscellaneous
    Miscellaneous
    
    Serverless QA Bot with S3 and Lambda
    
    Serverless QA Bot with Modal
  - JavaScript
    JavaScript
    
    Overview
    
    Serverless Website Chatbot
    
    YouTube Transcript Search
    
    TransformersJS Embedding Search
  - Rust
    Rust
    
    Overview
  - RAG
    RAG
    
    Vanilla RAG
    
    Multi-Head RAG
    
    Corrective RAG
    
    Agentic RAG
    
    Graph RAG
    
    Self RAG
    
    Adaptive RAG
    
    SFR RAG
    
    Advanced Techniques
    Advanced Techniques
    
    HyDE
    
    FLARE
API & SDK Reference
API & SDK Reference
- API Changes
- LanceDB Cloud REST API
- Client SDKs
  Client SDKs
  - Python SDK
  - JavaScript SDK
    JavaScript SDK
    
    Current SDK (@lancedb/lancedb)
    
    Legacy SDK (vectordb)
  - Rust SDK
Changelog
Changelog
- LanceDB Cloud & Enterprise
- ↗LanceDB Open Source
Studies
Studies

Table of contents

Index
- Classes
- Interfaces

@lancedb/lancedb • Docs

@lancedb/lancedb / rerankers

rerankers

Index

Classes

RRFReranker

Interfaces

Reranker

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