Movatterモバイル変換

URL:

画像なし夜間モード

Skip to content

LanceDB

Overview

Initializing search

lancedb/lancedb

Home
Quick start
Concepts
Guides
Managing Embeddings
Integrations
Examples
Studies
API reference

LanceDB

lancedb/lancedb

Home
Home
- LanceDB
- 🏃🏼‍♂️ Quick start
- 📚 Concepts
  📚 Concepts
  - Vector search
  - Indexing
    Indexing
    IVFPQ
    HNSW
  - Storage
  - Data management
- 🔨 Guides
  🔨 Guides
  - Working with tables
  - Building a vector index
  - Vector Search
  - Full-text search (native)
  - Full-text search (tantivy-based)
  - Building a scalar index
  - Hybrid search
    Hybrid search
    Overview
    Comparing Rerankers
    Airbnb financial data example
  - Late interaction with MultiVector search
    Late interaction with MultiVector search
    Overview
    Example
  - 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
  - Reranking
    Reranking
    Quickstart
    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
  - Filtering
  - Versioning & Reproducibility
    Versioning & Reproducibility
    sync API
    async API
  - Configuring Storage
  - Migration Guide
  - Tuning retrieval performance
    Tuning retrieval performance
    Choosing right query type
    Reranking
    Embedding fine-tuning
- 🧬 Managing embeddings
  🧬 Managing embeddings
  - Understand Embeddings
  - Get Started
  - Embedding functions
  - Available models
    Available models
    Overview
    Text Embedding Functions
    Text Embedding Functions
    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 Functions
    Multimodal Embedding Functions
    OpenClip embeddings
    Imagebind embeddings
    Jina Embeddings
  - User-defined embedding functions
  - Variables and secrets
  - Example: Multi-lingual semantic search
  - Example: MultiModal CLIP Embeddings
- 🔌 Integrations
  🔌 Integrations
  - Tools and data formats
  - Pandas and PyArrow
  - Polars
  - DuckDB
  - Datafusion
  - LangChain
    LangChain
    LangChain 🔗
    LangChain demo
    LangChain JS/TS 🔗
  - LlamaIndex 🦙
    LlamaIndex 🦙
    LlamaIndex docs
    LlamaIndex demo
  - Pydantic
  - Voxel51
  - PromptTools
  - dlt
  - phidata
  - Genkit
- 🎯 Examples
  🎯 Examples
  - Overview
  - 🐍 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
- 📓 Studies
  📓 Studies
  - ↗Improve retrievers with hybrid search and reranking
- 💭 FAQs
- 🔍 Troubleshooting
- ⚙️ API reference
  ⚙️ API reference
Quick start
Concepts
Concepts
- Vector search
- Indexing
  Indexing
  - IVFPQ
  - HNSW
- Storage
- Data management
Guides
Guides
- Working with tables
- Working with SQL
- Building an ANN index
- Vector Search
- Full-text search (native)
- Full-text search (tantivy-based)
- Building a scalar index
- Hybrid search
  Hybrid search
- Late interaction with MultiVector search
  Late interaction with MultiVector search
  - Overview
  - Multivector Search: Efficient Document Retrieval with ColPali and LanceDB
- 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
- Reranking
  Reranking
- Filtering
- Versioning & Reproducibility
  Versioning & Reproducibility
  - Sync API
  - Async API
- Configuring Storage
- Migration Guide
- Tuning retrieval performance
  Tuning retrieval performance
Managing Embeddings
Managing Embeddings
- Understand Embeddings
- Get Started
- Embedding functions
- Available models
  Available models
  - Overview
  - Text Embedding Functions
    Text Embedding Functions
    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
  - Multimodal Embedding Functions
    Multimodal Embedding Functions
    OpenClip embeddings
    Imagebind embeddings
    Jina Embeddings
- User-defined embedding functions
- Variables and secrets
- Example - Multi-lingual semantic search
- Example - MultiModal CLIP Embeddings
Integrations
Integrations
Examples
Examples
- Example projects and recipes
- 🐍 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
- 🦀 Rust
  🦀 Rust
  - Overview
Studies
Studies
- Overview
- ↗Improve retrievers with hybrid search and reranking
API reference
API reference

API Reference

The API reference for the LanceDB client SDKs are available at the following locations:

Python
JavaScript (legacy vectordb package)
JavaScript (newer @lancedb/lancedb package)
Rust

Made with Material for MkDocs

[8]ページ先頭

©2009-2025 Movatter.jp