🗃️ Data Index

Concept

An Index is a data structure that allows us to quickly retrieve relevant context for a user query. For LlamaIndex, it’s the core foundation for retrieval-augmented generation (RAG) use-cases.

At a high-level, Indices are built from Documents. They are used to build Query Engines and Chat Engines which enables question & answer and chat over your data.

Under the hood, Indices store data in Node objects (which represent chunks of the original documents), and expose an Retriever interface that supports additional configuration and automation.

Usage Pattern

Get started with:

from llama_index import VectorStoreIndex

index = VectorStoreIndex.from_documents(docs)

• Usage Pattern
  • Get Started
  • Configuring Document Parsing
  • Handling Document Update

Modules

• Module Guides
  • Vector Store Index
  • List Index
  • Tree Index
  • Keyword Table Index
  • Knowledge Graph Index
  • Pandas Index
  • SQL Index
  • Document Summary Index

Advanced Concepts

• Composability