In Depth
LlamaIndex (formerly GPT Index) is a framework focused on connecting large language models with external data. While LangChain provides general-purpose orchestration, LlamaIndex specializes in the data connection layer: ingesting data from diverse sources, building efficient indexes, and providing sophisticated query interfaces that enable LLMs to reason over private data.
The framework supports a wide range of data connectors (databases, APIs, documents, websites), index types (vector, keyword, tree, knowledge graph), and query strategies (simple retrieval, sub-question decomposition, recursive retrieval, multi-document agents). This makes it particularly well-suited for building RAG systems that need to work with complex, heterogeneous data sources.
LlamaIndex has expanded beyond simple RAG to support agentic RAG (where the retrieval strategy is dynamically chosen), multi-modal retrieval (combining text and images), and workflow orchestration. For businesses with large document collections or complex data environments, LlamaIndex provides production-grade tools for building AI applications that can intelligently search, summarize, and reason over their proprietary data.