LlamaIndex (RAG Framework)

⭐ 46.0k MIT Python 0.12.0

The top-choice framework for RAG tasks, featuring over 300 data connectors, more than 40 vector databases, and advanced retrieval strategies.

📋 Info

GitHub Stars⭐ 46.0k Stars
LicenseMIT
LanguagePython
Version0.12.0
Updated2026-06-01

📖 Overview

LlamaIndex is the preferred framework for building RAG applications. Its key advantage lies in its 300+ data connectors, which allow documents to be loaded from various sources such as PDFs, Word files, databases, APIs, Slack, Notion, and web pages. It supports 40+ vector libraries, offering a full range of retrieval strategies from basic to advanced. The platform also provides LlamaParse for professional document parsing. It works well in conjunction with LangChain. It is suitable for any scenario where AI needs to understand private data.

✨ Features

  • 300+ data connectors — connecting to any dataset source
  • Integration with over 40 vector databases
  • Multi-level retrieval strategies (semantic/mixed/recursive/AI agent).
  • LlamaParse for professional document parsing
  • Works in complementary partnership with LangChain.

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🚀 Quick Start

pip install llama-index-core
pip install llama-index-llms-openai

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