LlamaIndex is a data framework that helps developers connect large language models to external data sources for retrieval-augmented generation (RAG), knowledge management, and data-grounded AI applications. It provides data connectors, index structures, and query engines that simplify building production RAG systems. AI engineers building document Q&A systems, enterprise search applications, and data-grounded chatbots use LlamaIndex to handle the data ingestion, chunking, embedding, and retrieval pipeline. It supports 150+ data connectors for common data sources. LlamaIndex and LangChain are the two dominant open-source AI application frameworks, with LlamaIndex focusing specifically on the data layer (retrieval, indexing, and querying) while LangChain provides broader orchestration capabilities. Many production systems use both.

What the community says

AI engineers on Reddit r/MachineLearning and GitHub consider LlamaIndex a core tool for RAG development. Frequently paired with LangChain for different aspects of AI application architecture. Based on community discussions from Reddit and GitHub.

Join the discussion on Reddit →